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Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on urban areas in the past, whereas rural-background stations are normally less impacted by surrounding anthropogenic sources. Therefore, they are predisposed for studying the impact of long-range transport of anthropogenic aerosols. Here, the chemical composition and organic aerosol (OA) sources of submicron aerosol particles measured by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) were investigated at Melpitz from September 2016 to August 2017. The location of the station at the frontier between western and eastern Europe makes it the ideal place to investigate the impact of long-range transport over Europe. Indeed, the station is under the influence of less polluted air masses from westerly directions and more polluted continental air masses from eastern Europe. The OA dominated the submicron particle mass concentration and showed strong seasonal variability ranging from 39 % (in winter) to 58 % (in summer). It was followed by sulfate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using the rolling positive matrix factorization (PMF) approach to account for the potential temporal changes in the source profile. It was possible to split OA into five factors with a distinct temporal variability and mass spectral signature. Three were associated with anthropogenic primary OA (POA) sources: hydrocarbon-like OA (HOA; 5.2 % of OA mass in winter and 6.8 % in summer), biomass burning OA (BBOA; 10.6 % and 6.1 %) and coal combustion OA (CCOA; 23 % and 8.7 %). Another two are secondary and processed oxygenated OA (OOA) sources: less oxidized OOA (LO-OOA; 28.4 % and 36.7 %) and more oxidized OOA (MO-OOA; 32.8 % and 41.8 %). Since equivalent black carbon (eBC) was clearly associated with the identified POA factors (sum of HOA, BBOA, and CCOA; R2= 0. 87), eBC's contribution to each of the POA factors was achieved using a multilinear regression model. Consequently, CCOA represented the main anthropogenic sources of carbonaceous aerosol (sum of OA and eBC) not only during winter (56 % of POA in winter) but also in summer (13 % of POA in summer), followed by BBOA (29 % and 69 % of POA in winter and summer, respectively) and HOA (15 % and 18 % of POA in winter and summer, respectively). A seasonal air mass cluster analysis was used to understand the geographical origins of the different aerosol types and showed that during both winter and summer time, PM1 (PM with an aerodynamic diameter smaller than 1 µm) air masses with eastern influence were always associated with the highest mass concentration and the highest coal combustion fraction. Since during wintertime CCOA is a combination of domestic heating and power plant emissions, the summer contribution of CCOA emphasizes the critical importance of coal power plant emissions to rural-background aerosols and its impact on air quality, through long-range transportation.

To investigate the impact of aging on the sources, volatility, and viscosity of organic aerosol (OA) in Chinese outflows, a high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) coupled with a thermodenuder (TD) was deployed in the spring of 2018 in Dongying, which is a regional receptor site of metropolitan emissions in the North China Plain (NCP). The average mass concentration of PM1 is 31.5±22.7 µg m−3, which is mainly composed of nitrate (33 %) and OA (25 %). The source apportionment results show that the OA is mainly contributed by oxygenated OA (OOA) from secondary sources, including background-OOA (33 %) representing a background concentration of OA (2.6 µg m−3) in the NCP area, and transported-OOA (33 %) oxidized from urban emissions. The other two factors include aged hydrocarbon-liked OA (aged-HOA, 28 %) from transported vehicle emissions and biomass burning OA (BBOA, 5 %) from local open burning. The volatility of total OA (average C*=3.2×10-4 µg m−3) in this study is generally lower than that reported in previous field studies, which is mainly due to the high OA oxidation level resulting from aging processes during transport. The volatilities of OA factors follow the order of background-OOA (average C*=2.7×10-5 µg m−3) < transported-OOA (3.7×10-4µgm-3)< aged-HOA (8.1×10-4µgm-3)< BBOA (0.012 µg m−3). Extremely low volatilities in ambient air indicate that oligomers may exist in aged plumes. The viscosity estimation suggests that the majority of ambient OA in this study behaves as semisolid (60 %), liquifies at higher relative humidity (RH) (21 %), and solidifies (19 %) during noon when the RH is low and the oxidation level is high. Finally, the estimated mixing time of molecules in 200 nm OA varies dramatically from minutes at night to years in the afternoon, emphasizing the need to consider its dynamic kinetic limits when modeling OA. In general, the overall results of this study improve our understanding of the impact of aging on OA volatility and viscosity.

Kraków is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been made to characterize ambient aerosol, there is a lack of online and long-term measurements of non-refractory aerosol. Our measurements at the AGH University of Science and Technology provide the online long-term chemical composition of ambient submicron particulate matter (PM1) between January 2018 and April 2019. Here we report the chemical characterization of non-refractory submicron aerosol and source apportionment of the organic fraction by positive matrix factorization (PMF). In contrast to other long-term source apportionment studies, we let a small PMF window roll over the dataset instead of performing PMF over the full dataset or on separate seasons. In this way, the seasonal variation in the source profiles can be captured. The uncertainties in the PMF solutions are addressed by the bootstrap resampling strategy and the random a-value approach for constrained factors. We observe clear seasonal patterns in the concentration and composition of PM1, with high concentrations during the winter months and lower concentrations during the summer months. Organics are the dominant species throughout the campaign. Five organic aerosol (OA) factors are resolved, of which three are of a primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of a secondary nature (more oxidized oxygenated OA (MO-OOA) and less oxidized oxygenated OA (LO-OOA)). While HOA contributes on average 8.6 % ± 2.3 % throughout the campaign, the solid-fuel-combustion-related BBOA and CCOA show a clear seasonal trend with average contributions of 10.4 % ± 2.7 % and 14.1 %, ±2.1 %, respectively. Not only BBOA but also CCOA is associated with residential heating because of the pronounced yearly cycle where the highest contributions are observed during wintertime. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contributions of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively.

In the present work, we conducted experiments of secondary organic aerosol (SOA) formation from urban cooking and vehicular sources to characterize the mass spectral features of primary organic aerosol (POA) and SOA using an high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). Our results showed that the cooking styles have a greater impact on aged COA (cooking organic aerosol) mass spectra than oxidation conditions. However, the oxidation conditions affect the aged HOA (hydrocarbon-like OA) spectra more significantly than vehicle operating conditions. In our study, we use mass spectra similarity analysis and positive matrix factorization (PMF) analysis to establish the POA and SOA mass spectra of these two sources. These mass spectra are used as source constraints in a multilinear engine (ME-2) model to apportion the OA (organic aerosol) sources in the atmosphere. Compared with the traditional ambient PMF results, the improved ME-2 model can better quantify the contribution of POA and SOA from cooking and vehicular sources. Our work, for the first time, establishes the vehicle and cooking SOA source profiles, and can be further used in the OA source apportionment in the ambient atmosphere.

We collected 1 year of aerosol chemical speciation monitor (ACSM) data in Magadino, a village located in the south of the Swiss Alpine region, one of Switzerland's most polluted areas. We analysed the mass spectra of organic aerosol (OA) by positive matrix factorisation (PMF) using Source Finder Professional (SoFi Pro) to retrieve the origins of OA. Therein, we deployed a rolling algorithm, which is closer to the measurement, to account for the temporal changes in the source profiles. As the first-ever application of rolling PMF with multilinear engine (ME-2) analysis on a yearlong dataset that was collected from a rural site, we resolved two primary OA factors (traffic-related hydrocarbon-like OA (HOA) and biomass burning OA (BBOA)), one mass-to-charge ratio (m/z) 58-related OA (58-OA) factor, a less oxidised oxygenated OA (LO-OOA) factor, and a more oxidised oxygenated OA (MO-OOA) factor. HOA showed stable contributions to the total OA through the whole year ranging from 8.1 % to 10.1 %, while the contribution of BBOA showed an apparent seasonal variation with a range of 8.3 %–27.4 % (highest during winter, lowest during summer) and a yearly average of 17.1 %. OOA (sum of LO-OOA and MO-OOA) contributed 71.6 % of the OA mass, varying from 62.5 % (in winter) to 78 % (in spring and summer). The 58-OA factor mainly contained nitrogen-related variables which appeared to be pronounced only after the filament switched. However, since the contribution of this factor was insignificant (2.1 %), we did not attempt to interpolate its potential source in this work. The uncertainties (σ) for the modelled OA factors (i.e. rotational uncertainty and statistical variability in the sources) varied from ±4 % (58-OA) to a maximum of ±40 % (LO-OOA). Considering that BBOA and LO-OOA (showing influences of biomass burning in winter) had significant contributions to the total OA mass, we suggest reducing and controlling biomass-burning-related residential heating as a mitigation strategy for better air quality and lower PM levels in this region or similar locations. In Appendix A, we conduct a head-to-head comparison between the conventional seasonal PMF analysis and the rolling mechanism. We find similar or slightly improved results in terms of mass concentrations, correlations with external tracers, and factor profiles of the constrained POA factors. The rolling results show smaller scaled residuals and enhanced correlations between OOA factors and corresponding inorganic salts compared to those of the seasonal solutions, which was most likely because the rolling PMF analysis can capture the temporal variations in the oxidation processes for OOA components. Specifically, the time-dependent factor profiles of MO-OOA and LO-OOA can well explain the temporal viabilities of two main ions for OOA factors, m/z 44 (CO2+) and m/z 43 (mostly C2H3O+). Therefore, this rolling PMF analysis provides a more realistic source apportionment (SA) solution with time-dependent OA sources. The rolling results also show good agreement with offline Aerodyne aerosol mass spectrometer (AMS) SA results from filter samples, except for in winter. The latter discrepancy is likely because the online measurement can capture the fast oxidation processes of biomass burning sources, in contrast to the 24 h filter samples. This study demonstrates the strengths of the rolling mechanism, provides a comprehensive criterion list for ACSM users to obtain reproducible SA results, and is a role model for similar analyses of such worldwide available data.

We present 18 years (2001–2018) of aerosol measurements, including organic and elemental carbon (OC and EC), organic tracers (levoglucosan, arabitol, mannitol, trehalose, glucose, and 2-methyltetrols), trace elements, and ions, at the Birkenes Observatory (southern Norway) – a site representative of the northern European region. The OC/EC (2001–2018) and the levoglucosan (2008–2018) time series are the longest in Europe, with OC/EC available for the PM10, PM2.5 (fine), and PM10–2.5 (coarse) size fractions, providing the opportunity for a nearly 2-decade-long assessment. Using positive matrix factorization (PMF), we identify seven carbonaceous aerosol sources at Birkenes: mineral-dust-dominated aerosol (MIN), traffic/industry-like aerosol (TRA/IND), short-range-transported biogenic secondary organic aerosol (BSOASRT), primary biological aerosol particles (PBAP), biomass burning aerosol (BB), ammonium-nitrate-dominated aerosol (NH4NO3), and (one low carbon fraction) sea salt aerosol (SS). We observed significant (p), large decreases in EC in PM10 (−3.9 % yr−1) and PM2.5 (−4.2 % yr−1) and a smaller decline in levoglucosan (−2.8 % yr−1), suggesting that OC/EC from traffic and industry is decreasing, whereas the abatement of OC/EC from biomass burning has been slightly less successful. EC abatement with respect to anthropogenic sources is further supported by decreasing EC fractions in PM2.5 (−3.9 % yr−1) and PM10 (−4.5 % yr−1). PMF apportioned 72 % of EC to fossil fuel sources; this was further supported by PMF applied to absorption photometer data, which yielded a two-factor solution with a low aerosol Ångstrøm exponent (AAE = 0.93) fraction, assumed to be equivalent black carbon from fossil fuel combustion (eBCFF), contributing 78 % to eBC mass. The higher AAE fraction (AAE = 2.04) is likely eBC from BB (eBCBB). Source–receptor model calculations (FLEXPART) showed that continental Europe and western Russia were the main source regions of both elevated eBCBB and eBCFF. Dominating biogenic sources explain why there was no downward trend for OC. A relative increase in the OC fraction in PM2.5 (+3.2 % yr−1) and PM10 (+2.4 % yr−1) underscores the importance of biogenic sources at Birkenes (BSOA and PBAP), which were higher in the vegetative season and dominated both fine (53 %) and coarse (78 %) OC. Furthermore, 77 %–91 % of OC in PM2.5, PM10–2.5, and PM10 was attributed to biogenic sources in summer vs. 22 %–37 % in winter. The coarse fraction had the highest share of biogenic sources regardless of season and was dominated by PBAP, except in winter. Our results show a shift in the aerosol composition at Birkenes and, thus, also in the relative source contributions. The need for diverse offline and online carbonaceous aerosol speciation to understand carbonaceous aerosol sources, including their seasonal, annual, and long-term variability, has been demonstrated.

The formation and evolution of secondary organic aerosol (SOA) were investigated at Yorkville, GA, in late summer (mid-August to mid-October 2016). The organic aerosol (OA) composition was measured using two online mass spectrometry instruments, the high-resolution time-of-flight aerosol mass spectrometer (AMS) and the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct chemical ionization mass spectrometer (FIGAERO-CIMS). Through analysis of speciated organics data from FIGAERO-CIMS and factorization analysis of data obtained from both instruments, we observed notable SOA formation from isoprene and monoterpenes during both day and night. Specifically, in addition to isoprene epoxydiol (IEPOX) uptake, we identified isoprene SOA formation from non-IEPOX pathways and isoprene organic nitrate formation via photooxidation in the presence of NOx and nitrate radical oxidation. Monoterpenes were found to be the most important SOA precursors at night. We observed significant contributions from highly oxidized acid-like compounds to the aged OA factor from FIGAERO-CIMS. Taken together, our results showed that FIGAERO-CIMS measurements are highly complementary to the extensively used AMS factorization analysis, and together they provide more comprehensive insights into OA sources and composition.

The measurement of elements in PM10 was performed with 1 h time resolution at a rural freeway site during summer 2015 in Switzerland using the Xact1 625 Ambient Metals Monitor. On average the Xact elements (without accounting for oxygen and other associated elements) make up about 20 % of the total PM10 mass (14.6 µg m−3). We conducted source apportionment by positive matrix factorisation (PMF) of the elemental mass measurable by the Xact (i.e. major elements heavier than Al), defined here as PM10el. Eight different sources were identified in PM10el (elemental PM10) mass driven by the sum of 14 elements (notable elements in brackets): Fireworks-I (K, S, Ba and Cl), Fireworks-II (K), sea salt (Cl), secondary sulfate (S), background dust (Si, Ti), road dust (Ca), non-exhaust traffic-related elements (Fe) and industrial elements (Zn and Pb). The major components were secondary sulfate and non-exhaust traffic-related elements followed by background dust and road dust factors, explaining 21 %, 20 %, 18 % and 16 % of the analysed PM10 elemental mass, respectively, with the factor mass not corrected for oxygen content. Further, there were minor contributions (on the order of a few percent) of sea salt and industrial sources. The regionally influenced secondary sulfate factor showed negligible resuspension, and concentrations were similar throughout the day. The significant loads of the non-exhaust traffic-related and road dust factors with strong diurnal variations highlight the continuing importance of vehicle-related air pollutants at this site. Enhanced control of PMF implemented via the SourceFinder software (SoFi Pro version 6.2, PSI, Switzerland) allowed for a successful apportionment of transient sources such as the two firework factors and sea salt, which remained mixed when analysed by unconstrained PMF.

The Po Valley (Italy) is a well-known air quality hotspot characterized by particulate matter (PM) levels well above the limit set by the European Air Quality Directive and by the World Health Organization, especially during the colder season. In the framework of Emilia-Romagna regional project “Supersito”, the southern Po Valley submicron aerosol chemical composition was characterized by means of high-resolution aerosol mass spectroscopy (HR-AMS) with the specific aim of organic aerosol (OA) characterization and source apportionment. Eight intensive observation periods (IOPs) were carried out over 4 years (from 2011 to 2014) at two different sites (Bologna, BO, urban background, and San Pietro Capofiume, SPC, rural background), to characterize the spatial variability and seasonality of the OA sources, with a special focus on the cold season. On the multi-year basis of the study, the AMS observations show that OA accounts for averages of 45±8 % (ranging from 33 % to 58 %) and 46±7 % (ranging from 36 % to 50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and rural sites, respectively. Primary organic aerosol (POA) comprises biomass burning (23±13 % of OA) and fossil fuel (12±7 %) contributions with a marked seasonality in concentration. As expected, the biomass burning contribution to POA is more significant at the rural site (urban / rural concentration ratio of 0.67), but it is also an important source of POA at the urban site during the cold season, with contributions ranging from 14 % to 38 % of the total OA mass. Secondary organic aerosol (SOA) contributes to OA mass to a much larger extent than POA at both sites throughout the year (69±16 % and 83±16 % at the urban and rural sites, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning aging products during the cold season, even at the urban background site. This biomass burning SOA fraction represents 14 %–44 % of the total OA mass in the cold season, indicating that in this region a major contribution of combustion sources to PM mass is mediated by environmental conditions and atmospheric reactivity. Among the environmental factors controlling the formation of SOA in the Po Valley, the availability of liquid water in the aerosol was shown to play a key role in the cold season. We estimate that the organic fraction originating from aqueous reactions of biomass burning products (“bb-aqSOA”) represents 21 % (14 %–28 %) and 25 % (14 %–35 %) of the total OA mass and 44 % (32 %–56 %) and 61 % (21 %–100 %) of the SOA mass at the urban and rural sites, respectively.

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.

Organic aerosol (OA) particles are recognized as key factors influencing air quality and climate change. However, highly time-resolved long-term 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 an aerosol chemical speciation monitor (ACSM) and a multiwavelength Aethalometer from November 2011 to March 2018 at a peri-urban 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 in 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 −175 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 statistically significant trend for LO-OOA over the 6-year investigated period.

Bootstrap analysis is commonly used to capture the uncertainties of a bilinear receptor model such as the positive matrix factorization (PMF) model. This approach can estimate the factor-related uncertainties and partially assess the rotational ambiguity of the model. The selection of the environmentally plausible solutions, though, can be challenging, and a systematic approach to identify and sort the factors is needed. For this, comparison of the factors between each bootstrap run and the initial PMF output, as well as with externally determined markers, is crucial. As a result, certain solutions that exhibit suboptimal factor separation should be discarded. The retained solutions would then be used to test the robustness of the PMF output. Meanwhile, analysis of filter samples with the Aerodyne aerosol mass spectrometer and the application of PMF and bootstrap analysis on the bulk water-soluble organic aerosol mass spectra have provided insight into the source identification and their uncertainties. Here, we investigated a full yearly cycle of the sources of organic aerosol (OA) at three sites in Estonia: Tallinn (urban), Tartu (suburban) and Kohtla-Järve (KJ; industrial). We identified six OA sources and an inorganic dust factor. The primary OA types included biomass burning, dominant in winter in Tartu and accounting for 73 % ± 21 % of the total OA, primary biological OA which was abundant in Tartu and Tallinn in spring (21 % ± 8 % and 11 % ± 5 %, respectively), and two other primary OA types lower in mass. A sulfur-containing OA was related to road dust and tire abrasion which exhibited a rather stable yearly cycle, and an oil OA was connected to the oil shale industries in KJ prevailing at this site that comprises 36 % ± 14 % of the total OA in spring. The secondary OA sources were separated based on their seasonal behavior: a winter oxygenated OA dominated in winter (36 % ± 14 % for KJ, 25 % ± 9 % for Tallinn and 13 % ± 5 % for Tartu) and was correlated with benzoic and phthalic acid, implying an anthropogenic origin. A summer oxygenated OA was the main source of OA in summer at all sites (26 % ± 5 % in KJ, 41 % ± 7 % in Tallinn and 35 % ± 7 % in Tartu) and exhibited high correlations with oxidation products of a-pinene-like pinic acid and 3-methyl-1, 2, 3-butanetricarboxylic acid (MBTCA), suggesting a biogenic origin.

Biogenic volatile organic compound (BVOC) emissions are one of the essential inputs for chemical transport models (CTMs), but their estimates are associated with large uncertainties, leading to significant influence on air quality modelling. This study aims to investigate the effects of using different BVOC emission models on the performance of a CTM in simulating secondary pollutants, i.e. ozone, organic, and inorganic aerosols. European air quality was simulated for the year 2011 by the regional air quality model Comprehensive Air Quality Model with Extensions (CAMx) version 6.3, using BVOC emissions calculated by two emission models: the Paul Scherrer Institute (PSI) model and the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1. Comparison of isoprene and monoterpene emissions from both models showed large differences in their general amounts, as well as their spatial distribution in both summer and winter. MEGAN produced more isoprene emissions by a factor of 3 while the PSI model generated 3 times the monoterpene emissions in summer, while there was negligible difference (∼4 %) in sesquiterpene emissions associated with the two models. Despite the large differences in isoprene emissions (i.e. 3-fold), the resulting impact in predicted summertime ozone proved to be minor (<10 %; MEGAN O3 was higher than PSI O3 by ∼7 ppb). Comparisons with measurements from the European air quality database (AirBase) indicated that PSI emissions might improve the model performance at low ozone concentrations but worsen performance at high ozone levels (>60 ppb). A much larger effect of the different BVOC emissions was found for the secondary organic aerosol (SOA) concentrations. The higher monoterpene emissions (a factor of ∼3) by the PSI model led to higher SOA by ∼110 % on average in summer, compared to MEGAN, and lead to better agreement between modelled and measured organic aerosol (OA): the mean bias between modelled and measured OA at nine measurement stations using Aerodyne aerosol chemical speciation monitors (ACSMs) or Aerodyne aerosol mass spectrometers (AMSs) was reduced by 21 %–83 % at rural or remote stations. Effects on inorganic aerosols (particulate nitrate, sulfate, and ammonia) were relatively small (<15 %).

The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83±8 % of variation in data, which increased to 96±3 % when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35±7 % of mass), low and semi-volatile oxidised organic aerosols (27±8 % and 12±7 %), biomass burning organic aerosol (11±7 %), a nitrate-containing organic aerosol type (7±2 %), ammonium nitrate (5±2 %), and hydrocarbon-like organic aerosol (3±1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ion-balance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statistics-based approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data.

Particulate matter (PM) pollution is a severe environmental problem in the Beijing–Tianjin–Hebei (BTH) region in North China. PM studies have been conducted extensively in Beijing, but the chemical composition, sources, and atmospheric processes of PM are still relatively less known in nearby Tianjin and Hebei. In this study, fine PM in urban Shijiazhuang (the capital of Hebei Province) was characterized using an Aerodyne quadrupole aerosol chemical speciation monitor (Q-ACSM) from 11 January to 18 February in 2014. The average mass concentration of non-refractory submicron PM (diameter  µm, NR-PM1) was 178±101 µg m−3, and it was composed of 50 % organic aerosol (OA), 21 % sulfate, 12 % nitrate, 11 % ammonium, and 6 % chloride. Using the multilinear engine (ME-2) receptor model, five OA sources were identified and quantified, including hydrocarbon-like OA from vehicle emissions (HOA, 13 %), cooking OA (COA, 16 %), biomass burning OA (BBOA, 17 %), coal combustion OA (CCOA, 27 %), and oxygenated OA (OOA, 27 %). We found that secondary formation contributed substantially to PM in episodic events, whereas primary emissions were dominant (most significant) on average. The episodic events with the highest NR-PM1 mass range of 300–360 µg m−3 were comprised of 55 % of secondary species. On the contrary, a campaign-average low OOA fraction (27 %) in OA indicated the importance of primary emissions, and a low sulfur oxidation degree (FSO4) of 0.18 even at RH >90 % hinted at insufficient oxidation. These results suggested that in Shijiazhuang in wintertime fine PM was mostly from primary emissions without sufficient atmospheric aging, indicating opportunities for air quality improvement by mitigating direct emissions. In addition, secondary inorganic and organic (OOA) species dominated in pollution events with high-RH conditions, most likely due to enhanced aqueous-phase chemistry, whereas primary organic aerosol (POA) dominated in pollution events with low-RH and stagnant conditions. These results also highlighted the importance of meteorological conditions for PM pollution in this highly polluted city in North China.

The North China Plain (NCP) has experienced frequent severe haze pollution events in recent years. While extensive measurements have been made in megacities, aerosol sources, processes, and particle growth at urban downwind sites remain less understood. Here, an aerosol chemical speciation monitor and a scanning mobility particle sizer, along with a suite of collocated instruments, were deployed at the downwind site of Xingtai, a highly polluted city in the NCP, for real-time measurements of submicron aerosol (PM1) species and particle number size distributions during May and June 2016. The average mass concentration of PM1 was 30.5 (±19.4) µg m−3, which is significantly lower than that during wintertime. Organic aerosols (OAs) constituted the major fraction of PM1 (38 %), followed by sulfate (25 %) and nitrate (14 %). Positive matrix factorization with the multilinear engine version 2 showed that oxygenated OA (OOA) was the dominant species in OA throughout the study, on average accounting for 78 % of OA, while traffic and cooking emissions both accounted for 11 % of OA. Our results highlight that aerosol particles at the urban downwind site were highly aged and mainly from secondary formation. However, the diurnal cycle also illustrated the substantial influence of urban emissions on downwind sites, which are characterized by similar pronounced early morning peaks for most aerosol species. New particle formation and growth events were also frequently observed (58 % of the time) on both clean and polluted days. Particle growth rates varied from 1.2 to 4.9 nm h−1 and our results showed that sulfate and OOA played important roles in particle growth during clean periods, while OOA was more important than sulfate during polluted events. Further analyses showed that particle growth rates have no clear dependence on air mass trajectories.

Organic aerosol (OA) represents a large fraction of submicron aerosols in the megacity of Beijing, yet long-term characterization of its sources and variations is very limited. Here we present an analysis of in situ measurements of OA in submicrometer particles with an aerosol chemical speciation monitor (ACSM) for 2 years from July 2011 to May 2013. The sources of OA are analyzed with a multilinear engine (ME-2) by constraining three primary OA factors including fossil-fuel-related OA (FFOA), cooking OA (COA), and biomass burning OA (BBOA). Two secondary OAs (SOA), representing a less oxidized oxygenated OA (LO-OOA) and a more oxidized (MO-OOA), are identified during all seasons. The monthly average concentration OA varied from 13.6 to 46.7 µg m−3 with a strong seasonal pattern that is usually highest in winter and lowest in summer. FFOA and BBOA show similarly pronounced seasonal variations with much higher concentrations and contributions in winter due to enhanced coal combustion and biomass burning emissions. The contribution of COA to OA, however, is relatively stable (10–15 %) across different seasons, yet presents significantly higher values at low relative humidity levels (RH T) conditions. Comparatively, MO-OOA shows high concentrations consistently at high RH levels across different T levels, and the contribution of MO-OOA to OA is different seasonally with lower values occurring more in winter (30–34 %) than other seasons (47–64 %). Overall, SOA ( = LO-OOA + MO-OOA) dominates OA composition during all seasons by contributing 52–64 % of the total OA mass in the heating season and 65–75 % in non-heating seasons. The variations in OA composition as a function of OA mass loading further illustrate the dominant role of SOA in OA across different mass loading scenarios during all seasons. However, we also observed a large increase in FFOA associated with a corresponding decrease in MO-OOA during periods with high OA mass loadings in the heating season, illustrating an enhanced role of coal combustion emissions during highly polluted episodes. Potential source contribution function analysis further shows that the transport from the regions located to the south and southwest of Beijing within ∼ 250 km can contribute substantially to high FFOA and BBOA concentrations in the heating season.

Despite extensive efforts toward the characterization of submicron aerosols at ground level in the megacity of Beijing, our understanding of aerosol sources and processes at high altitudes remains low. Here we conducted a 3-month real-time measurement of non-refractory submicron aerosol (NR-PM1) species at a height of 260 m from 10 October 2014 to 18 January 2015 using an aerosol chemical speciation monitor. Our results showed a significant change in aerosol composition from the non-heating period (NHP) to the heating period (HP). Organics and chloride showed clear increases during HP due to coal combustion emissions, while nitrate showed substantial decreases from 28 to 15–18 %. We also found that NR-PM1 species in the heating season can have average mass differences of 30–44 % under similar emission sources yet different meteorological conditions. Multi-linear engine 2 (ME-2) using three primary organic aerosol (OA) factors as constraints, i.e., fossil-fuel-related OA (FFOA) dominantly from coal combustion emissions, cooking OA (COA), and biomass burning OA (BBOA) resolved from ground high-resolution aerosol mass spectrometer measurements, was applied to OA mass spectra of ACSM. Two types of secondary OA (SOA) that were well correlated with nitrate and chloride–CO, respectively, were identified. SOA played a dominant role in OA during all periods at 260 m although the contributions were decreased from 72 % during NHP to 58–64 % during HP. The SOA composition also changed significantly from NHP to HP. While the contribution of oxygenated OA (OOA) was decreased from 56–63 to 32–40 %, less oxidized OOA (LO-OOA) showed a large increase from 9–16 to 24–26 %. COA contributed a considerable fraction of OA at high altitude, and the contribution was relatively similar across different periods (10–13 %). In contrast, FFOA showed a large increase during HP due to the influences of coal combustion emissions. We also observed very different OA composition between ground level and 260 m. Particularly, the contributions of COA and BBOA at the ground site were nearly twice those at 260 m, while SOA at 260 m was ∼ 15–34 % higher than that at ground level. Bivariate polar plots and back-trajectory analysis further illustrated the different source regions of OA factors in different seasons.

Long-term monitoring of 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 using an aerosol mass spectrometer (AMS) to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline AMS measurements for particulate matter smaller than 10 µm at nine 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 positive matrix factorization, PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA 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 an anthropogenic secondary inorganic species that is dominant in winter (winter oxygenated OA, WOOA). A factor (sulfur-containing organic, SC-OA) explaining sulfur-containing fragments (CH3SO2+), which has an event-driven temporal behaviour, was also identified. The relative yearly average factor contributions range from 4 to 14 % for HOA, from 3 to 11 % for COA, from 11 to 59 % for BBOA, from 5 to 23 % for SC-OA, from 14 to 27 % for WOOA, and from 15 to 38 % for SOOA. The uncertainty of the relative average factor contribution lies between 2 and 12 % 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 87 % in alpine valleys and 42 % north of the alpine crest. Furthermore, the influence of primary biological particles (PBOAs), not resolved by PMF, is estimated and could contribute significantly to OA in PM10.

The present study offers the first chemical characterization of the submicron (PM1) fraction in western Africa at a high time resolution, thanks to collocated measurements of nonrefractory (NR) species with an Aerosol Chemical Speciation Monitor (ACSM), black carbon and iron concentrations derived from absorption coefficient measurements with a 7-wavelength Aethalometer, and total PM1 determined by a TEOM-FDMS (tapered element oscillating microbalance–filtered dynamic measurement system) for mass closure. The field campaign was carried out over 3 months (March to June 2015) as part of the SHADOW (SaHAran Dust Over West Africa) project at a coastal site located in the outskirts of the city of Mbour, Senegal. With an averaged mass concentration of 5.4 µg m−3, levels of NR PM1 in Mbour were 3 to 10 times lower than those generally measured in urban and suburban polluted environments. Nonetheless the first half of the observation period was marked by intense but short pollution events (NR PM1 concentrations higher than 15 µg m−3), sea breeze phenomena and Saharan desert dust outbreaks (PM10 up to 900 µg m−3). During the second half of the campaign, the sampling site was mainly under the influence of marine air masses. The air masses on days under continental and sea breeze influences were dominated by organics (36–40 %), whereas sulfate particles were predominant (40 %) for days under oceanic influence. Overall, measurements showed that about three-quarters of the total PM1 were explained by NR PM1, BC (black carbon) and Fe (a proxy for dust) concentrations, leaving approximately one-quarter for other refractory species. A mean value of 4.6 % for the Fe ∕ PM1 ratio was obtained. Source apportionment of the organic fraction, using positive matrix factorization (PMF), highlighted the impact of local combustion sources, such as traffic and residential activities, which contribute on average to 52 % of the total organic fraction. A new organic aerosol (OA) source, representing on average 3 % of the total OA fraction, showed similar variation to nonrefractory particulate chloride. Its rose plot and daily pattern pointed to local combustion processes, i.e., two open waste-burning areas located about 6 and 11 km away from the receptor site and to a lesser extent a traditional fish-smoking location. The remaining fraction was identified as oxygenated organic aerosols (OOA), a factor that prevailed regardless of the day type (45 %) and was representative of regional (approximately three-quarters) but also local (approximately one-quarter) sources due to enhanced photochemical processes.

Particulate matter (PM) pollution on the peripheries of Chinese megacities can be as serious as in cities themselves. Given the substantial vehicular emissions in inner-city areas, the direct transport of primary PM (e.g., black carbon and primary organics) and effective formation of secondary PM from precursors (e.g., NOx and volatile organic compounds) can contribute to PM pollution in buffer zones between cities. To investigate how traffic emissions in inner-city areas impact these adjacent buffer zones, a suite of real-time instruments were deployed in Panyu, downwind from central Guangzhou, from November to December 2014. Nitrate mass fraction was higher on high-PM days, with the average nitrate-to-sulfate ratio increasing from around 0.35 to 1.5 as the PM mass concentration increased from 10 to 160 µg m−3. Particulate nitrate was strongly correlated with excess ammonium (([NH4+] ∕ [SO42−] − 1.5) × [SO42−]), with higher concentrations in December than in November due to lower temperatures. The organic mass fraction was the highest across all PM1 levels throughout the campaign. While organic aerosols (OA) were dominated by secondary organic aerosols (SOA = semi-volatile oxygenated organic aerosols + low-volatility oxygenated organic aerosols) as a campaign average, freshly emitted hydrocarbon-like organic aerosols (HOA) contributed up to 40 % of OA during high-OA periods, which typically occurred at nighttime and contributed 23.8 to 28.4 % on average. This was due to daytime traffic restrictions on heavy-duty vehicles in Guangzhou, and HOA almost increased linearly with total OA concentration. SOA increased as odd oxygen (Ox = O3 + NO2) increased during the day due to photochemistry. A combination of nighttime traffic emissions and daytime photochemistry contributed to the buildup of PM in Panyu. The mitigation of PM pollution in inner-city areas by reducing vehicular traffic can potentially improve air quality in peripheral areas.

The North China Plain (NCP) frequently experiences heavy haze pollution, particularly during wintertime. In winter 2015–2016, the NCP region suffered several extremely severe haze episodes with air pollution red alerts issued in many cities. We have investigated the sources and aerosol evolution processes of the severe pollution episodes in Handan, a typical industrialized city in the NCP region, using real-time measurements from an intensive field campaign during the winter of 2015–2016. The average (±1σ) concentration of submicron aerosol (PM1) during 3 December 2015–5 February 2016 was 187.6 (±137.5) µg m−3, with the hourly maximum reaching 700.8 µg m−3. Organic was the most abundant component, on average accounting for 45 % of total PM1 mass, followed by sulfate (15 %), nitrate (14 %), ammonium (12 %), chloride (9 %) and black carbon (BC, 5 %). Positive matrix factorization (PMF) with the multilinear engine (ME-2) algorithm identified four major organic aerosol (OA) sources, including traffic emissions represented by a hydrocarbon-like OA (HOA, 7 % of total OA), industrial and residential burning of coal represented by a coal combustion OA (CCOA, 29 % of total OA), open and domestic combustion of wood and crop residuals represented by a biomass burning OA (BBOA, 25 % of total OA), and formation of secondary OA (SOA) in the atmosphere represented by an oxygenated OA (OOA, 39 % of total OA). Emissions of primary OA (POA), which together accounted for 61 % of total OA and 27 % of PM1, are a major cause of air pollution during the winter. Our analysis further uncovered that primary emissions from coal combustion and biomass burning together with secondary formation of sulfate (mainly from SO2 emitted by coal combustion) are important driving factors for haze evolution. However, the bulk composition of PM1 showed comparatively small variations between less polluted periods (daily PM2. 5 ≤ 75 µg m−3) and severely polluted periods (daily PM2. 5 > 75 µg m−3), indicating relatively synchronous increases of all aerosol species during haze formation. The case study of a severe haze episode, which lasted 8 days starting with a steady buildup of aerosol pollution followed by a persistently high level of PM1 (326.7–700.8 µg m−3), revealed the significant influence of stagnant meteorological conditions which acerbate air pollution in the Handan region. The haze episode ended with a shift of wind which brought in cleaner air masses from the northwest of Handan and gradually reduced PM1 concentration to −3 after 12 h. Aqueous-phase reactions under higher relative humidity (RH) were found to significantly promote the production of secondary inorganic species (especially sulfate) but showed little influence on SOA.

Mass spectrometric measurements commonly yield data on hundreds of variables over thousands of points in time. Refining and synthesizing this raw data into chemical information necessitates the use of advanced, statistics-based data analytical techniques. In the field of analytical aerosol chemistry, statistical, dimensionality reductive methods have become widespread in the last decade, yet comparable advanced chemometric techniques for data classification and identification remain marginal. Here we present an example of combining data dimensionality reduction (factorization) with exploratory classification (clustering), and show that the results cannot only reproduce and corroborate earlier findings, but also complement and broaden our current perspectives on aerosol chemical classification. We find that applying positive matrix factorization to extract spectral characteristics of the organic component of air pollution plumes, together with an unsupervised clustering algorithm, k-means+ + , for classification, reproduces classical organic aerosol speciation schemes. Applying appropriately chosen metrics for spectral dissimilarity along with optimized data weighting, the source-specific pollution characteristics can be statistically resolved even for spectrally very similar aerosol types, such as different combustion-related anthropogenic aerosol species and atmospheric aerosols with similar degree of oxidation. In addition to the typical oxidation level and source-driven aerosol classification, we were also able to classify and characterize outlier groups that would likely be disregarded in a more conventional analysis. Evaluating solution quality for the classification also provides means to assess the performance of mass spectral similarity metrics and optimize weighting for mass spectral variables. This facilitates algorithm-based evaluation of aerosol spectra, which may prove invaluable for future development of automatic methods for spectra identification and classification. Robust, statistics-based results and data visualizations also provide important clues to a human analyst on the existence and chemical interpretation of data structures. Applying these methods to a test set of data, aerosol mass spectrometric data of organic aerosol from a boreal forest site, yielded five to seven different recurring pollution types from various sources, including traffic, cooking, biomass burning and nearby sawmills. Additionally, three distinct, minor pollution types were discovered and identified as amine-dominated aerosols.

Lanzhou, which is located in a steep alpine valley in western China, is one of the most polluted cities in China during the wintertime. In this study, an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a seven-wavelength aethalometer, and a scanning mobility particle sizer (SMPS) were deployed during 10 January to 4 February 2014 to study the mass concentrations, chemical processes, and sources of submicrometer particulate matter (PM1). The average PM1 concentration during this study was 57.3 µg m−3 (ranging from 2.1 to 229.7 µg m−3 for hourly averages), with organic aerosol (OA) accounting for 51.2 %, followed by nitrate (16.5 %), sulfate (12.5 %), ammonium (10.3 %), black carbon (BC, 6.4 %), and chloride (3.0 %). The mass concentration of PM1 during winter was more than twice the average value observed at the same site in summer 2012 (24.5 µg m−3), but the mass fraction of OA was similar in the two seasons. Nitrate contributed a significantly higher fraction to the PM1 mass in winter than summer (16.5 % vs. 10 %), largely due to more favored partitioning to the particle phase at low air temperature. The mass fractions of both OA and nitrate increased by ∼ 5 % (47 to 52 for OA and 13 to 18 % for nitrate) with the increase of the total PM1 mass loading, while the average sulfate fraction decreased by 6 % (17 to 11 %), indicating the importance of OA and nitrate for the heavy air pollution events in Lanzhou. The size distributions of OA, nitrate, sulfate, ammonium, and chloride all peaked at ∼ 500 nm, with OA being slightly broader, suggesting that aerosol particles were internally mixed during winter, likely due to frequently calm and stagnant air conditions during wintertime in Lanzhou (average wind speed: 0.82 m s−1).The average mass spectrum of OA showed a medium oxidation degree (average O ∕ C ratio of 0.28), which was lower than that during summer 2012 (O ∕ C = 0.33). This is consistent with weaker photochemical processing during winter. Positive matrix factorization (PMF) with the multi-linear engine (ME-2) solver identified six OA sources, i.e., a hydrocarbon-like OA (HOA), a biomass burning OA (BBOA), a cooking-emitted OA (COA), a coal combustion OA (CCOA), and two oxygenated OA (OOA) factors. One of the OOAs was less oxidized (LO-OOA), and the other one more oxidized (MO-OOA). LO-OOA was the most abundant OA component (22.3 % of OA mass), followed by CCOA (22.0 %), COA (20.2 %), MO-OOA (14.9 %), BBOA (10.8 %), and HOA (9.8 %). The mass fraction of primary OA ( = HOA + BBOA + COA + CCOA) increased during high PM pollution periods, indicating that local primary emissions were a main reason for the formation of air pollution events in Lanzhou during winter. Radiocarbon (14C) measurement was conducted on four PM2.5 filter samples from this study, which allowed for a quantitative source apportionment of organic carbon (OC). The non-fossil sources on average accounted for 55 ± 3 % of OC, which could be mainly from biomass burning and cooking activities, suggesting the importance of non-fossil sources for the PM pollution in Lanzhou. Together with the PMF results, we also found that a large fraction (66 ± 10 %) of the secondary OC was from non-fossil OC.

The multilinear engine (ME-2) factorization tool is being widely used following the recent development of the Source Finder (SoFi) interface at the Paul Scherrer Institute. However, the success of this tool, when using the a value approach, largely depends on the inputs (i.e. target profiles) applied as well as the experience of the user. A strategy to explore the solution space is proposed, in which the solution that best describes the organic aerosol (OA) sources is determined according to the systematic application of predefined statistical tests. This includes trilinear regression, which proves to be a useful tool for comparing different ME-2 solutions. Aerosol Chemical Speciation Monitor (ACSM) measurements were carried out at the urban background site of North Kensington, London from March to December 2013, where for the first time the behaviour of OA sources and their possible environmental implications were studied using an ACSM. Five OA sources were identified: biomass burning OA (BBOA), hydrocarbon-like OA (HOA), cooking OA (COA), semivolatile oxygenated OA (SVOOA) and low-volatility oxygenated OA (LVOOA). ME-2 analysis of the seasonal data sets (spring, summer and autumn) showed a higher variability in the OA sources that was not detected in the combined March–December data set; this variability was explored with the triangle plots f44 : f43 f44 : f60, in which a high variation of SVOOA relative to LVOOA was observed in the f44 : f43 analysis. Hence, it was possible to conclude that, when performing source apportionment to long-term measurements, important information may be lost and this analysis should be done to short periods of time, such as seasonally. Further analysis on the atmospheric implications of these OA sources was carried out, identifying evidence of the possible contribution of heavy-duty diesel vehicles to air pollution during weekdays compared to those fuelled by petrol.

Fine particulate matter (PM) levels and resulting impacts on human health are in the Po Valley (Italy) among the highest in Europe. To build effective PM abatement strategies, it is necessary to characterize fine PM chemical composition, sources and atmospheric processes on long timescales (> months), with short time resolution (1) with a time resolution of 30 min at the regional background site of Ispra during 1 full year, using the Aerodyne Aerosol Chemical Speciation Monitor (ACSM) under the most up-to-date and stringent quality assurance protocol. The identification of the main components of the organic fraction is made using the Multilinear-Engine 2 algorithm implemented within the latest version of the SoFi toolkit. In addition, with the aim of a potential implementation of ACSM measurements in European air quality networks as a replacement of traditional filter-based techniques, parallel multiple offline analyses were carried out to assess the performance of the ACSM in the determination of PM chemical species regulated by air quality directives. The annual NR-PM1 level monitored at the study site (14.2 µg m−3) is among the highest in Europe and is even comparable to levels reported in urban areas like New York City and Tokyo. On the annual basis, submicron particles are primarily composed of organic aerosol (OA, 58 % of NR-PM1). This fraction was apportioned into oxygenated OA (OOA, 66 %), hydrocarbon-like OA (HOA, 11 % of OA) and biomass burning OA (BBOA, 23 %). Among the primary sources of OA, biomass burning (23 %) is thus bigger than fossil fuel combustion (11 %). Significant contributions of aged secondary organic aerosol (OOA) are observed throughout the year. The unexpectedly high degree of oxygenation estimated during wintertime is probably due to the contribution of secondary BBOA and the enhancement of aqueous-phase production of OOA during cold months. BBOA and nitrate are the only components of which contributions increase with the NR-PM1 levels. Therefore, biomass burning and NOx emission reductions would be particularly efficient in limiting submicron aerosol pollution events. Abatement strategies conducted during cold seasons appear to be more efficient than annual-based policies. In a broader context, further studies using high-time-resolution analytical techniques on a long-term basis for the characterization of fine aerosol should help better shape our future air quality policies, which constantly need refinement.

Highly oxidized multifunctional compounds (HOMs) have been demonstrated to be important for atmospheric secondary organic aerosols (SOA) and new-particle formation (NPF), yet it remains unclear which the main atmospheric HOM formation pathways are. In this study, a nitrate-ion-based chemical ionization atmospheric-pressure-interface time-of-flight mass spectrometer (CI-APi-TOF) was deployed to measure HOMs in the boreal forest in Hyytiälä, southern Finland. Positive matrix factorization (PMF) was applied to separate the detected HOM species into several factors, relating these “factors” to plausible formation pathways. PMF was performed with a revised error estimation derived from laboratory data, which agrees well with an estimate based on ambient data. Three factors explained the majority (> 95 %) of the data variation, but the optimal solution found six factors, including two nighttime factors, three daytime factors, and a transport factor. One nighttime factor is almost identical to laboratory spectra generated from monoterpene ozonolysis, while the second likely represents monoterpene oxidation initiated by NO3. The exact chemical processes forming the different daytime factors remain unclear, but they all have clearly distinct diurnal profiles, very likely related to monoterpene oxidation with a strong influence from NO, presumably through its effect on peroxy radical (RO2) chemistry. Apart from these five “local” factors, the sixth factor is interpreted as a transport related factor. These findings improve our understanding of HOM production by confirming current knowledge and inspiring future research directions and provide new perspectives on using factorization methods to understand short-lived atmospheric species.

Isoprene-epoxydiols-derived secondary organic aerosol (IEPOX-SOA) can contribute substantially to organic aerosol (OA) concentrations in forested areas under low NO conditions, hence significantly influencing the regional and global OA budgets, accounting, for example, for 16–36 % of the submicron OA in the southeastern United States (SE US) summer. Particle evaporation measurements from a thermodenuder show that the volatility of ambient IEPOX-SOA is lower than that of bulk OA and also much lower than that of known monomer IEPOX-SOA tracer species, indicating that IEPOX-SOA likely exists mostly as oligomers in the aerosol phase. The OH aging process of ambient IEPOX-SOA was investigated with an oxidation flow reactor (OFR). New IEPOX-SOA formation in the reactor was negligible, as the OFR does not accelerate processes such as aerosol uptake and reactions that do not scale with OH. Simulation results indicate that adding ∼ 100 µg m−3 of pure H2SO4 to the ambient air allows IEPOX-SOA to be efficiently formed in the reactor. The heterogeneous reaction rate coefficient of ambient IEPOX-SOA with OH radical (kOH) was estimated as 4.0 ± 2.0 × 10−13 cm3 molec−1 s−1, which is equivalent to more than a 2-week lifetime. A similar kOH was found for measurements of OH oxidation of ambient Amazon forest air in an OFR. At higher OH exposures in the reactor (> 1 × 1012 molec cm−3 s), the mass loss of IEPOX-SOA due to heterogeneous reaction was mainly due to revolatilization of fragmented reaction products. We report, for the first time, OH reactive uptake coefficients (γOH = 0.59 ± 0.33 in SE US and γOH = 0.68 ± 0.38 in Amazon) for SOA under ambient conditions. A relative humidity dependence of kOH and γOH was observed, consistent with surface-area-limited OH uptake. No decrease of kOH was observed as OH concentrations increased. These observations of physicochemical properties of IEPOX-SOA can help to constrain OA impact on air quality and climate.

Intensive measurements of submicron aerosol particles and their chemical composition were performed with an Aerosol Chemical Speciation Monitor (ACSM) at the Cabauw Experimental Site for Atmospheric Research (CESAR) in Cabauw, the Netherlands, sampling at 5 m height above ground. The campaign lasted nearly 1 year from July 2012 to June 2013 as part of the EU-FP7-ACTRIS project (Q-ACSM Network). Including equivalent black carbon an average particulate mass concentration of 9.50 µg m−3 was obtained during the whole campaign with dominant contributions from ammonium nitrate (45 %), organic aerosol (OA, 29 %), and ammonium sulfate (19 %). There were 12 exceedances of the World Health Organization (WHO) PM2.5 daily mean limit (25 µg m−3) observed at this rural site using PM1 instrumentation only. Ammonium nitrate and OA represented the largest contributors to total particulate matter during periods of exceedance. Source apportionment of OA was performed season-wise by positive matrix factorization (PMF) using the multilinear engine 2 (ME-2) controlled via the source finder (SoFi). Primary organic aerosols were attributed mainly to traffic (8–16 % contribution to total OA, averaged season-wise) and biomass burning (0–23 %). Secondary organic aerosols (SOAs, 61–84 %) dominated the organic fraction during the whole campaign, particularly on days with high mass loadings. A SOA factor which is attributed to humic-like substances (HULIS) was identified as a highly oxidized background aerosol in Cabauw. This shows the importance of atmospheric aging processes for aerosol concentration at this rural site. Due to the large secondary fraction, the reduction of particulate mass at this rural site is challenging on a local scale.

In early spring the Baltic region is frequently affected by high-pollution events due to biomass burning in that area. Here we present a comprehensive study to investigate the impact of biomass/grass burning (BB) on the evolution and composition of aerosol in Preila, Lithuania, during springtime open fires. Non-refractory submicron particulate matter (NR-PM1) was measured by an Aerodyne aerosol chemical speciation monitor (ACSM) and a source apportionment with the multilinear engine (ME-2) running the positive matrix factorization (PMF) model was applied to the organic aerosol fraction to investigate the impact of biomass/grass burning. Satellite observations over regions of biomass burning activity supported the results and identification of air mass transport to the area of investigation. Sharp increases in biomass burning tracers, such as levoglucosan up to 683 ng m−3 and black carbon (BC) up to 17 µg m−3 were observed during this period. A further separation between fossil and non-fossil primary and secondary contributions was obtained by coupling ACSM PMF results and radiocarbon (14C) measurements of the elemental (EC) and organic (OC) carbon fractions. Non-fossil organic carbon (OCnf) was the dominant fraction of PM1, with the primary (POCnf) and secondary (SOCnf) fractions contributing 26–44 % and 13–23 % to the total carbon (TC), respectively. 5–8 % of the TC had a primary fossil origin (POCf), whereas the contribution of fossil secondary organic carbon (SOCf) was 4–13 %. Non-fossil EC (ECnf) and fossil EC (ECf) ranged from 13–24 and 7–13 %, respectively. Isotope ratios of stable carbon and nitrogen isotopes were used to distinguish aerosol particles associated with solid and liquid fossil fuel burning.

During winter 2013–2014 aerosol mass spectrometer (AMS) measurements were conducted for the first time with a novel PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 µm) lens in two major cities of China: Xi'an and Beijing. We denote the periods with visibility below 2 km as extreme haze and refer to the rest as reference periods. During the measurements in Xi'an an extreme haze covered the city for about a week and the total non-refractory (NR)-PM2.5 mass fraction reached peak concentrations of over 1000 µg m−3. During the measurements in Beijing two extreme haze events occurred, but the temporal extent and the total concentrations reached during these events were lower than in Xi'an. Average PM2.5 concentrations of 537 ± 146 and 243 ± 47 µg m−3 (including NR species and equivalent black carbon, eBC) were recorded during the extreme haze events in Xi'an and Beijing, respectively. During the reference periods the measured average concentrations were 140 ± 99 µg m−3 in Xi'an and 75 ± 61 µg m−3 in Beijing. The relative composition of the NR-PM2.5 evolved substantially during the extreme haze periods, with increased contributions of the inorganic components (mostly sulfate and nitrate). Our results suggest that the high relative humidity present during the extreme haze events had a strong effect on the increase of sulfate mass (via aqueous phase oxidation of sulfur dioxide). Another relevant characteristic of the extreme haze is the size of the measured particles. During the extreme haze events, the AMS showed much larger particles, with a volume weighted mode at about 800 to 1000 nm, in contrast to about 400 nm during reference periods. These large particle sizes made the use of the PM2.5 inlet crucial, especially during the severe haze events, where 39 ± 5 % of the mass would have been lost in the conventional PM1 (particulate matter with aerodynamic diameter ≤ 1 µm) inlet. A novel positive matrix factorization procedure was developed to apportion the sources of organic aerosols (OA) based on their mass spectra using the multilinear engine (ME-2) controlled via the source finder (SoFi). The procedure allows for an effective exploration of the solution space, a more objective selection of the best solution and an estimation of the rotational uncertainties. Our results clearly show an increase of the oxygenated organic aerosol (OOA) mass during extreme haze events. The contribution of OOA to the total OA increased from the reference to the extreme haze periods from 16.2 ± 1.1 to 31.3 ± 1.5 % in Xi'an and from 15.7 ± 0.7 to 25.0 ± 1.2 % in Beijing. By contrast, during the reference periods the total OA mass was dominated by domestic emissions of primary aerosols from biomass burning in Xi'an (42.2 ± 1.5 % of OA) and coal combustion in Beijing (55.2 ± 1.6 % of OA). These two sources are also mostly responsible for extremely high polycyclic aromatic hydrocarbon (PAH) concentrations measured with the AMS (campaign average of 2.1 ± 2.0 µg m−3 and frequent peak concentrations above 10 µg m−3). To the best of our knowledge, this is the first data set where the simultaneous extraction of these two primary sources could be achieved in China by conducting on-line AMS measurements at two areas with contrasted emission patterns.

Chemically resolved (organic, nitrate, sulfate, ammonium) data of non-refractory submicron (NR-PM1) aerosol from the first long-term deployment (27 July 2012 to 02 October 2013) of a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) at the Swiss high-altitude site Jungfraujoch (JFJ; 3580 m a.s.l.) are presented. Besides total mass loadings, diurnal variations and relative species contributions during the different meteorological seasons, geographical origin and sources of organic aerosol (OA) are discussed. Backward transport simulations show that the highest (especially sulfate) concentrations of NR-PM1 were measured in air masses advected to the station from regions south of the JFJ, while lowest concentrations were seen from western regions. OA source apportionment for each season was performed using the Source Finder (SoFi) interface for the multilinear engine (ME-2). OA was dominated in all seasons by oxygenated OA (OOA, 71–88 %), with lesser contributions from local tourism-related activities (7–12 %) and hydrocarbon-like OA related to regional vertical transport (3–9 %). In summer the OOA can be separated into a background low-volatility OA (LV-OOA I, possibly associated with long-range transport) and a slightly less oxidised low-volatility OA (LV-OOA II) associated with regional vertical transport. Wood burning-related OA associated with regional transport was detected during the whole winter 2012/2013 and during rare events in summer 2013, in the latter case attributed to small-scale transport for the surrounding valleys. Additionally, the data were divided into periods with free tropospheric (FT) conditions and periods with planetary boundary layer (PBL) influence, enabling the assessment of the composition for each. Most nitrate and part of the OA are injected from the regional PBL, while sulfate is mainly produced in the FT. The south/north gradient of sulfate is also pronounced in FT air masses (sulfate mass fraction from the south: 45 %; from the north: 29 %). Furthermore, a detailed investigation of specific marker fragments of the OA spectra (f43, f44, f55, f57, f60) showed different degrees of ageing depending on season.

Trace element measurements in PM10–2.5, PM2.5–1.0 and PM1.0–0.3 aerosol were performed with 2 h time resolution at kerbside, urban background and rural sites during the ClearfLo winter 2012 campaign in London. The environment-dependent variability of emissions was characterized using the Multilinear Engine implementation of the positive matrix factorization model, conducted on data sets comprising all three sites but segregated by size. Combining the sites enabled separation of sources with high temporal covariance but significant spatial variability. Separation of sizes improved source resolution by preventing sources occurring in only a single size fraction from having too small a contribution for the model to resolve. Anchor profiles were retrieved internally by analysing data subsets, and these profiles were used in the analyses of the complete data sets of all sites for enhanced source apportionment. A total of nine different factors were resolved (notable elements in brackets): in PM10–2.5, brake wear (Cu, Zr, Sb, Ba), other traffic-related (Fe), resuspended dust (Si, Ca), sea/road salt (Cl), aged sea salt (Na, Mg) and industrial (Cr, Ni); in PM2.5–1.0, brake wear, other traffic-related, resuspended dust, sea/road salt, aged sea salt and S-rich (S); and in PM1.0–0.3, traffic-related (Fe, Cu, Zr, Sb, Ba), resuspended dust, sea/road salt, aged sea salt, reacted Cl (Cl), S-rich and solid fuel (K, Pb). Human activities enhance the kerb-to-rural concentration gradients of coarse aged sea salt, typically considered to have a natural source, by 1.7–2.2. These site-dependent concentration differences reflect the effect of local resuspension processes in London. The anthropogenically influenced factors traffic (brake wear and other traffic-related processes), dust and sea/road salt provide further kerb-to-rural concentration enhancements by direct source emissions by a factor of 3.5–12.7. The traffic and dust factors are mainly emitted in PM10–2.5 and show strong diurnal variations with concentrations up to 4 times higher during rush hour than during night-time. Regionally influenced S-rich and solid fuel factors, occurring primarily in PM1.0–0.3, have negligible resuspension influences, and concentrations are similar throughout the day and across the regions.

Aerosol chemical speciation monitor (ACSM) measurements were performed in Zurich, Switzerland, for 13 months (February 2011 through February 2012). Many previous studies using this or related instruments have utilized the fraction of organic mass measured at m/z 44 (f44), which is typically dominated by the CO2+ ion and related to oxygenation, as an indicator of atmospheric aging. The current study demonstrates that during summer afternoons, when photochemical processes are most vigorous as indicated by high oxidant – OX (O3 + NO2), f44 for ambient secondary organic aerosol (SOA) is not higher but is rather similar or lower than on days with low OX. On the other hand, f43 (less oxidized fragment) tends to increase. These changes are discussed in the f44 / f43 space frequently used to interpret ACSM and aerosol mass spectrometer (AMS) data. This is likely due to the formation of semi-volatile oxygenated aerosol produced from biogenic precursor gases, whose emissions increase with ambient temperature. In addition, source apportionment analyses conducted on winter and summer data using positive matrix factorization (PMF) yield semi-volatile oxygenated organic aerosol (SV-OOA) factors that retain source-related chemical information. Winter SV-OOA is highly influenced by biomass burning, whereas summer SV-OOA is to a high degree produced from biogenic precursor gases. These sources contribute to substantial differences between the winter and summer f44 / f43 data, suggesting that PMF analysis of multi-season data employing only two OOA factors cannot capture the seasonal variability of OOA.

An Aerosol Chemical Speciation Monitor (ACSM, Aerodyne Research Inc.) was deployed at the Montseny (MSY; 41° 46'46" N, 02° 21'29" E, 720 m a.s.l.) regional background site in the western Mediterranean, Spain, from June 2012 to July 2013 to measure real-time inorganic (nitrate, sulfate, ammonium and chloride) and organic submicron aerosol concentrations. Co-located measurements, including real-time submicron particulate matter (PM1) and black carbon (BC) concentrations, and off-line PM1 chemical analysis were also carried out. This is one of the few studies that compare ACSM data with off-line PM1 measurements, avoiding the tail of the coarse mode included in the PM2.5 fraction. The ACSM + BC concentrations agreed with the PM1 measurements, and a strong correlation was found between the concentrations of ACSM species and the off-line measurements, although some discrepancies remain unexplained. Results point to a current underestimation of the relative ionization efficiency (RIE) established for organic aerosol (OA), which should be revised in the future. The OA was the major component of submicron aerosol (53% of PM1), with a higher contribution in summer (58% of PM1) than in winter (45% of PM1). Source apportionment of OA was carried out by applying positive matrix factorization (PMF), using the multilinear engine (ME-2) to the organic mass spectral data matrix. Three sources were identified in summer: hydrocarbon-like OA (HOA), low-volatile oxygenated OA (LV-OOA), and semi-volatile oxygenated OA (SV-OOA). The secondary OA (SOA; 4.8 μg m−3, sum of LV-OOA and SV-OOA) accounted for 85% of the total OA, and its formation during daytime (mainly SV-OOA) was estimated to be 1.1 μg m−3. In winter, HOA was also identified (12% of OA), a contribution from biomass burning OA (BBOA) was included and it was not possible to differentiate between two different SOA factors, but a single oxygenated OA (OOA) factor was resolved. The OOA contribution represented 60% of the total OA, with a degree of oxidation higher than both OOA summer factors. An intense wildfire episode was studied, obtaining a region-specific BBOA profile.

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 μm) 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.

Atmospheric submicron particulate matter (PM1) is one of the most significant pollution components in China. Despite its current popularity in the studies of aerosol chemistry, the characteristics, sources and evolution of atmospheric PM1 species are still poorly understood in China, particularly for the two harvest seasons, namely, the summer wheat harvest and autumn rice harvest. An Aerodyne Aerosol Chemical Speciation Monitor (ACSM) was deployed for online monitoring of PM1 components during summer and autumn harvest seasons in urban Nanjing, in the Yangtze River delta (YRD) region of China. PM1 components were shown to be dominated by organic aerosol (OA, 39 and 41%) and nitrate (23 and 20%) during the harvest seasons (the summer and autumn harvest). Positive matrix factorization (PMF) analysis of the ACSM OA mass spectra resolved four OA factors: hydrocarbon-like mixed with cooking-related OA (HOA + COA), fresh biomass-burning OA (BBOA), oxidized biomass-burning-influenced OA (OOA-BB), and highly oxidized OA (OOA); in particular the oxidized BBOA contributes ~80% of the total BBOA loadings. Both fresh and oxidized BBOA exhibited apparent diurnal cycles with peak concentration at night, when the high ambient relative humidity and low temperature facilitated the partitioning of semi-volatile organic species into the particle phase. The fresh BBOA concentrations for the harvests are estimated as BBOA = 15.1 × (m/z 60–0.26% × OA), where m/z (mass-to-charge ratio) 60 is a marker for levoglucosan-like species. The (BBOA + OOA-BB)/ΔCO, (ΔCO is the CO minus background CO), decreases as a function of f44 (fraction of m/z 44 in OA signal), which might indicate that BBOA was oxidized to less volatile OOA, e.g., more aged and low volatility OOA (LV-OOA) during the aging process. Analysis of air mass back trajectories indicates that the high BB pollutant concentrations are linked to the air masses from the western (summer harvest) and southern (autumn harvest) areas.

During winter 2013, extremely high concentrations (i.e., 4–20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) mass concentrations (24 h samples) were found in four major cities in China including Xi'an, Beijing, Shanghai and Guangzhou. Statistical analysis of a combined data set from elemental carbon (EC), organic carbon (OC), 14C and biomass-burning marker measurements using Latin hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. Based on 14C measurements of EC fractions (six samples each city), we found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% across all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xi'an (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10 and 48 ± 9% of OC and total carbon (TC), respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8, 48 ± 18, 53 ± 4 and 65 ± 26% of non-fossil OC for Xi'an, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately to heavily polluted days according to particulate matter mass. Despite a significant increase of the absolute mass concentrations of primary emissions from both fossil and non-fossil sources during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.

Online non-refractory submicron aerosol mass spectrometer (AMS) measurements in urban areas have successfully allowed the apportionment of specific sources and/or physical and chemical properties of the organic fraction. However, in order to be fully representative of PM pollution, a comprehensive source apportionment analysis is needed by taking into account all major components of submicron aerosols, creating strengthened bonds between the organic components and pollution sources. We present here a novel two-step methodology to perform such an analysis, by taking advantage of high time resolution of monitoring instruments: the aerosol chemical speciation monitor (ACSM) and the multi-wavelength absorption measurements (Aethalometer AE31) in Paris, France. As a first step, organic aerosols (OA) were deconvolved to hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and oxygenated OA (OOA) with positive matrix factorization (PMF), and black carbon was deconvolved into its wood burning and fossil fuel combustion fractions. A second PMF analysis was then carried out with organic factors, BC fractions and inorganic species (nitrate, sulfate, ammonium, chloride), leading to a four-factor solution allowing highly time-resolved characterization of the major sources of PM1. Outputs of this PMF2 include two dominant combustion sources (wood burning and traffic) as well as semi-volatile and low-volatile secondary aerosols. While HOA is found to be emitted by both wood burning and traffic, the latter sources occurred to significantly contribute also to OOA.

A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.

In the fine-particle mode (aerodynamic diameter < 1 μm) non-volatile material has been associated with black carbon (BC) and low-volatile organics and, to a lesser extent, with sea salt and mineral dust. This work analyzes non-volatile particles at the tropospheric research station Melpitz (Germany), combining experimental methods such as a mobility particle-size spectrometer (3–800 nm), a thermodenuder operating at 300 °C, a multi-angle absorption photometer (MAAP), and an aerosol mass spectrometer (AMS). The data were collected during two atmospheric field experiments in May–June 2008 as well as February–March 2009. As a basic result, we detected average non-volatile particle–volume fractions of 11 ± 3% (2008) and 17 ± 8% (2009). In both periods, BC was in close linear correlation with the non-volatile fraction, but not sufficient to quantitatively explain the non-volatile particle mass concentration. Based on the assumption that BC is not altered by the heating process, the non-volatile particle mass fraction could be explained by the sum of black carbon (47% in summer, 59% in winter) and a non-volatile organic contribution estimated as part of the low-volatility oxygenated organic aerosol (LV-OOA) (53% in summer, 41% in winter); the latter was identified from AMS data by factor analysis. Our results suggest that LV-OOA was more volatile in summer (May–June 2008) than in winter (February–March 2009) which was linked to a difference in oxidation levels (lower in summer). Although carbonaceous compounds dominated the sub-μm non-volatile particle mass fraction most of the time, a cross-sensitivity to partially volatile aerosol particles of maritime origin could be seen. These marine particles could be distinguished, however from the carbonaceous particles by a characteristic particle volume–size distribution. The paper discusses the uncertainty of the volatility measurements and outlines the possible merits of volatility analysis as part of continuous atmospheric aerosol measurements.

Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.

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 nighttime. 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 (black carbon) measurements and positive matrix factorization (PMF) analysis of the ACSM organic 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 (aerosol mass spectrometry) 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 periods with significant fire influence.

The MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) experiment took place in July 2009. The aim of this campaign was to study the aging and reactions of aerosol and gas-phase emissions in the city of Paris. Three ground-based measurement sites and several mobile platforms including instrument equipped vehicles and the ATR-42 aircraft were involved. We present here the variations in particle- and gas-phase species over the city of Paris, using a combination of high-time resolution measurements aboard the ATR-42 aircraft. Particle chemical composition was measured using a compact time-of-flight aerosol mass spectrometer (C-ToF-AMS), giving detailed information on the non-refractory submicron aerosol species. The mass concentration of black carbon (BC), measured by a particle absorption soot photometer (PSAP), was used as a marker to identify the urban pollution plume boundaries. Aerosol mass concentrations and composition were affected by air-mass history, with air masses that spent longest time over land having highest fractions of organic aerosol and higher total mass concentrations. The Paris plume is mainly composed of organic aerosol (OA), BC, and nitrate aerosol, as well as high concentrations of anthropogenic gas-phase species such as toluene, benzene, and NOx. Using BC and CO as tracers for air-mass dilution, we observe the ratio of ΔOA / ΔBC and ΔOA / ΔCO increase with increasing photochemical age (−log(NOx / NOy)). Plotting the equivalent ratios of different organic aerosol species (LV-OOA, SV-OOA, and HOA) illustrate that the increase in OA is a result of secondary organic aerosol (SOA) formation. Within Paris the changes in the ΔOA / ΔCO are similar to those observed during other studies in London, Mexico City, and in New England, USA. Using the measured SOA volatile organic compounds (VOCs) species together with organic aerosol formation yields, we were able to predict ~50% of the measured organics. These airborne measurements during the MEGAPOLI experiment show that urban emissions contribute to the formation of OA and have an impact on aerosol composition on a regional scale.

Secondary organic aerosol (SOA), a prominent fraction of particulate organic mass (OA), remains poorly constrained. Its formation involves several unknown precursors, formation and evolution pathways and multiple natural and anthropogenic sources. Here a combined gas-particle phase source apportionment is applied to wintertime and summertime data collected in the megacity of Paris in order to investigate SOA origin during both seasons. This was possible by combining the information provided by an aerosol mass spectrometer (AMS) and a proton transfer reaction mass spectrometer (PTR-MS). A better constrained apportionment of primary OA (POA) sources is also achieved using this methodology, making use of gas-phase tracers. These tracers made possible the discrimination between biogenic and continental/anthropogenic sources of SOA. We found that continental SOA was dominant during both seasons (24–50% of total OA), while contributions from photochemistry-driven SOA (9% of total OA) and marine emissions (13% of total OA) were also observed during summertime. A semi-volatile nighttime component was also identified (up to 18% of total OA during wintertime). This approach was successfully applied here and implemented in a new source apportionment toolkit.

In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

Detailed investigations of the chemical and microphysical properties of atmospheric aerosol particles were performed at the puy-de-Dôme (pdD) research station (1465 m) in autumn (September and October 2008), winter (February and March 2009), and summer (June 2010) using a compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). Over the three campaigns, the average mass concentrations of the non-refractory submicron particles ranged from 10 μg m−3 up to 27 μg m−3. Highest nitrate and ammonium mass concentrations were measured during the winter and during periods when marine modified airmasses were arriving at the site, whereas highest concentrations of organic particles were measured during the summer and during periods when continental airmasses arrived at the site. The measurements reported in this paper show that atmospheric particle composition is strongly influenced by both the season and the origin of the airmass. The total organic mass spectra were analysed using positive matrix factorisation to separate individual organic components contributing to the overall organic particle mass concentrations. These organic components include a low volatility oxygenated organic aerosol particle (LV-OOA) and a semi-volatile organic aerosol particle (SV-OOA). Correlations of the LV-OOA components with fragments of m/z 60 and m/z 73 (mass spectral markers of wood burning) during the winter campaign suggest that wintertime LV-OOA are related to aged biomass burning emissions, whereas organic aerosol particles measured during the summer are likely linked to biogenic sources. Equivalent potential temperature calculations, gas-phase, and LIDAR measurements define whether the research site is in the planetary boundary layer (PBL) or in the free troposphere (FT)/residual layer (RL). We observe that SV-OOA and nitrate particles are associated with air masses arriving from the PBL where as particle composition measured from RL/FT airmasses contain high mass fractions of sulphate and LV-OOA. This study provides unique insights into the effects of season and airmass variability on regional aerosol particles measured at an elevated site.