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Carbonaceous particulate matter (PM), comprising black carbon (BC), primary organic aerosol (POA) and secondary organic aerosol (SOA, from atmospheric aging of precursors), is a highly toxic vehicle exhaust component. Therefore, understanding vehicle pollution requires knowledge of both primary emissions, and how these emissions age in the atmosphere. We provide a systematic examination of carbonaceous PM emissions and parameterisation of SOA formation from modern diesel and gasoline cars at different temperatures (22, −7 °C) during controlled laboratory experiments. Carbonaceous PM emission and SOA formation is markedly higher from gasoline than diesel particle filter (DPF) and catalyst-equipped diesel cars, more so at −7 °C, contrasting with nitrogen oxides (NO X ). Higher SOA formation from gasoline cars and primary emission reductions for diesels implies gasoline cars will increasingly dominate vehicular total carbonaceous PM, though older non-DPF-equipped diesels will continue to dominate the primary fraction for some time. Supported by state-of-the-art source apportionment of ambient fossil fuel derived PM, our results show that whether gasoline or diesel cars are more polluting depends on the pollutant in question, i.e. that diesel cars are not necessarily worse polluters than gasoline cars.

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.

Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2.5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 µm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 µg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved long-term data sets.

While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g., often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter (OM) (34 ± 13%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69 to 85 and 80 to 95% for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~ 30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary wood burning, was on average 42 ± 13 and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that residential wood burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps (most likely because of differences in burning technologies) for these two regions in Switzerland.

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.

Co-occurrences of high concentrations of PM2.5 and ozone (O3) have been frequently observed in haze-aggravating processes in the North China Plain (NCP) over the past few years. Higher O3 concentrations on hazy days were hypothesized to be related to nitrous acid (HONO), but the key sources of HONO enhancing O3 during haze-aggravating processes remain unclear. We added six potential HONO sources, i.e., four ground-based (traffic, soil, and indoor emissions, and the NO2 heterogeneous reaction on ground surface (Hetground)) sources, and two aerosol-related (the NO2 heterogeneous reaction on aerosol surfaces (Hetaerosol) and nitrate photolysis (Photnitrate)) sources into the WRF-Chem model and designed 23 simulation scenarios to explore the unclear key sources. The results indicate that ground-based HONO sources producing HONO enhancements showed a rapid decrease with height, while the NO + OH reaction and aerosol-related HONO sources decreased slowly with height. Photnitrate contributions to HONO concentrations were enhanced with aggravated pollution levels. The enhancement of HONO due to Photnitrate on hazy days was about 10 times greater than on clean days and Photnitrate dominated daytime HONO sources (∼ 30 %–70 % when the ratio of the photolysis frequency of nitrate (Jnitrate) to gas nitric acid (JHNO3) equals 30) at higher layers (>800 m). Compared with that on clean days, the Photnitrate contribution to the enhanced daily maximum 8 h averaged (DMA8) O3 was increased by over 1 magnitude during the haze-aggravating process. Photnitrate contributed only ∼ 5 % of the surface HONO in the daytime with a Jnitrate/JHNO3 ratio of 30 but contributed ∼ 30 %–50 % of the enhanced O3 near the surface in NCP on hazy days. Surface O3 was dominated by volatile organic compound-sensitive chemistry, while O3 at higher altitudes (>800 m) was dominated by NOx-sensitive chemistry. Photnitrate had a limited impact on nitrate concentrations (<15 %) even with a Jnitrate/JHNO3 ratio of 120. These results suggest the potential but significant impact of Photnitrate on O3 formation, and that more comprehensive studies on Photnitrate in the atmosphere are still needed.

Secondary aerosols are a major component of PM2.5, yet their formation mechanisms in the ambient atmosphere are still unclear. Based on field measurements in downtown Beijing, we show that the photolysis of nitrous acid (HONO) may promote the formation of organic and nitrate aerosols in winter in Beijing, which is supported by the fact that the mass concentrations of organic and nitrate aerosols linearly increase as a function of HONO consumed from early morning to noon. The increased nitrate content also leads to the formation of ammonium particulate matter through enhancing the neutralization of nitrate and sulfate by ammonia. We further illustrate that during pollution events in winter in Beijing, over 50 % of the ambient HONO may be related to traffic-related emissions, including direct emissions and formation via the reaction between OH and vehicle-emitted NO. Overall, our results indicate that traffic-related HONO may play an important role in the oxidative capacity and in turn contribute to haze formation in winter in Beijing. The mitigation of HONO and NOx emissions from vehicles may be an effective way to reduce the formation of secondary aerosols and severe haze events in winter in Beijing.

Carbonaceous aerosols are related to adverse human health effects. Therefore, identification of their sources and analysis of their chemical composition is important. The offline AMS (aerosol mass spectrometer) technique offers quantitative separation of organic aerosol (OA) factors which can be related to major OA sources, either primary or secondary. While primary OA can be more clearly separated into sources, secondary (SOA) source apportionment is more challenging because different sources – anthropogenic or natural, fossil or non-fossil – can yield similar highly oxygenated mass spectra. Radiocarbon measurements provide unequivocal separation between fossil and non-fossil sources of carbon. Here we coupled these two offline methods and analysed the OA and organic carbon (OC) of different size fractions (particulate matter below 10 and 2.5 µm – PM10 and PM2.5, respectively) from the Alpine valley of Magadino (Switzerland) during the years 2013 and 2014 (219 samples). The combination of the techniques gave further insight into the characteristics of secondary OC (SOC) which was rather based on the type of SOC precursor and not on the volatility or the oxidation state of OC, as typically considered. Out of the primary sources separated in this study, biomass burning OC was the dominant one in winter, with average concentrations of 5.36 ± 2.64 µg m−3 for PM10 and 3.83 ± 1.81 µg m−3 for PM2.5, indicating that wood combustion particles were predominantly generated in the fine mode. The additional information from the size-segregated measurements revealed a primary sulfur-containing factor, mainly fossil, detected in the coarse size fraction and related to non-exhaust traffic emissions with a yearly average PM10 (PM2.5) concentration of 0.20 ± 0.24 µg m−3 (0.05 ± 0.04 µg m−3). A primary biological OC (PBOC) was also detected in the coarse mode peaking in spring and summer with a yearly average PM10 (PM2.5) concentration of 0.79 ± 0.31 µg m−3 (0.24 ± 0.20 µg m−3). The secondary OC was separated into two oxygenated, non-fossil OC factors which were identified based on their seasonal variability (i.e. summer and winter oxygenated organic carbon, OOC) and a third anthropogenic OOC factor which correlated with fossil OC mainly peaking in winter and spring, contributing on average 13 % ± 7 % (10 % ± 9 %) to the total OC in PM10 (PM2.5). The winter OOC was also connected to anthropogenic sources, contributing on average 13 % ± 13 % (6 % ± 6 %) to the total OC in PM10 (PM2.5). The summer OOC (SOOC), stemming from oxidation of biogenic emissions, was more pronounced in the fine mode, contributing on average 43 % ± 12 % (75 % ± 44 %) to the total OC in PM10 (PM2.5). In total the non-fossil OC significantly dominated the fossil OC throughout all seasons, by contributing on average 75 % ± 24 % to the total OC. The results also suggested that during the cold period the prevailing source was residential biomass burning while during the warm period primary biological sources and secondary organic aerosol from the oxidation of biogenic emissions became important. However, SOC was also formed by aged fossil fuel combustion emissions not only in summer but also during the rest of the year.

Understanding the chemical composition and sources of organic aerosol (OA) in the Arctic is critical given its importance for particle climate-relevant properties. This study presents a year-long analysis (May 2019–June 2020) of PM1 filter samples collected in Ny-Ålesund, Svalbard. A multi-instrumental approach is employed to characterize the comprehensive chemical composition of PM1, with a specific focus on its water-soluble organic fraction depicted combining proton nuclear magnetic resonance spectroscopy (H-NMR) and high-resolution time-of-flight aerosol mass spectrometry (HR-TOF-AMS), which provide complementary insights into the nature and structure of the organic aerosol classes characterizing the bulk OA mixture. Positive matrix factorization (PMF) source apportionment identifies consistent OA sources from the H-NMR and AMS datasets, showing a pronounced seasonality in their relative contributions to total OA mass. Winter–spring aerosol is dominated by long-range transport of Eurasian anthropogenic pollution (up to 70 %), while summer is characterized by biogenic aerosols from marine sources (up to 44 %), including sulfur compounds, amines, and fatty acids. Occasional summertime high OA loadings are associated with wildfire aerosols enriched in levoglucosan and humic-like substances (HULIS; averagely 27 %–28 %). Eventually, about 28 %–40 % of the OA mass is attributed to an unresolved mixture of extremely oxidized compounds of difficult specific source attribution. This integrated approach provides valuable insights into the seasonal dynamics of OA sources in the Arctic.

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.