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Fine particulate matter (PM 2.5) pollution is still one of China's most important environmental issues, especially in northern cities during wintertime. In this study, intensive real-time measurement campaigns were conducted in Xi'an, Shijiazhuang, and Beijing to investigate the chemical characteristics and source contributions of PM 2.5 and explore the formation of heavy pollution for policy implications. The chemical compositions of PM 2.5 in the three cities were all dominated by organic aerosol (OA) and nitrate (NO 3-). Results of source apportionment analyzed by a hybrid environmental receptor model (HERM) showed that the secondary formation source contributed more to PM 2.5 compared to other primary sources. Biomass burning was the dominant primary source in the three pilot cities. The contribution of coal combustion to PM 2.5 is non-negligible in Xi'an and Shijiazhuang but is no longer an important contributor in the capital city of Beijing due to the execution of a strict coal-banning policy. The potential formation mechanisms of secondary aerosol in the three cities were further explored by establishing the correlations between the secondary formation sources and aerosol liquid water content (ALWC) and Ox (O3+NO2) , respectively. The results showed that photochemical oxidation and aqueous-phase reaction were two important pathways of secondary aerosol formation. According to source variations, air pollution events that occurred in campaigns were classified into three types: biomass-combustion-dominated, secondary-formation-source-dominated, and a combination of primary and secondary sources. Additionally, this study compares the changes in chemical composition and source contributions of PM 2.5 in past decades. The results suggest that the clean-energy replacements for rural households should be urgently encouraged to reduce the primary source emissions in northern China, and collaborative control on ozone and particulate matter needs to be continuously promoted to weaken the atmosphere oxidation capacity for the sake of reducing secondary aerosol formation. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM2.5) pollution is still one of China's most important environmental issues, especially in northern cities during wintertime. In this study, intensive real-time measurement campaigns were conducted in Xi'an, Shijiazhuang, and Beijing to investigate the chemical characteristics and source contributions of PM2.5 and explore the formation progress of heavy pollution for policy implications. The chemical compositions of PM2.5 in the three cities were all dominated by organic aerosol (OA) and nitrate (NO3-). Results of source apportionment analyzed by the hybrid environmental receptor model (HERM) showed that the secondary nitrate plus sulfate contributed higher to PM2.5 compared to other primary sources. Biomass burning was the dominant primary source in the three pilot cities. The contribution of coal combustion to PM2.5 is non-negligible in Xi'an and Shijiazhuang but is no longer the important contributor in the capital city of Beijing due to the execution of a strict coal-banning policy. The potential formation mechanisms of secondary aerosol in three cities were further explored by establishing the correlations between the secondary nitrate plus sulfate and aerosol liquid water content (ALWC), and O x (O3 + NO2), respectively. The results showed that photochemical oxidation and aqueous-phase reaction were two important pathways of secondary aerosol formation. According to the source variations, air pollution events that occurred in campaigns were classified into three types: biomass combustion dominated, secondary nitrate plus sulfate dominated, and a combination of primary and secondary sources. Additionally, this study compared the changes in chemical composition and source contributions of PM2.5 in past decades. The results suggested that the clean energy replacements for the rural household should be urgently encouraged to reduce the primary source emissions in northern China, and collaborative control on ozone and particulate matter need to be continuously promoted to weaken the atmosphere oxidation capacity for the sake of reducing secondary aerosol formation. [ABSTRACT FROM AUTHOR]

Source apportionment studies have struggled to quantitatively link secondary organic aerosols (SOAs) to their precursor sources due largely to instrument limitations. For example, aerosol mass spectrometer (AMS) provides quantitative measurements of the total SOA fraction but lacks the chemical resolution to resolve most SOA sources. In contrast, instruments based on soft ionisation techniques, such as extractive electrospray ionisation mass spectrometry (EESI, e.g. the EESI time-of-flight mass spectrometer, EESI-TOF), have demonstrated the resolution to identify specific SOA sources but provide only a semi-quantitative apportionment due to uncertainties in the dependence of instrument sensitivity on molecular identity. We address this challenge by presenting a method for positive matrix factorisation (PMF) analysis on a single dataset which includes measurements from both AMS and EESI-TOF instruments, denoted "combined PMF" (cPMF). Because each factor profile includes both AMS and EESI-TOF components, the cPMF analysis maintains the source resolution capability of the EESI-TOF while also providing quantitative factor mass concentrations. Therefore, the bulk EESI-TOF sensitivity to each factor can also be directly determined from the analysis. We present metrics for ensuring that both instruments are well represented in the solution, a method for optionally constraining the profiles of factors that are detectable by one or both instruments, and a protocol for uncertainty analysis. As a proof of concept, the cPMF analysis was applied to summer and winter measurements in Zurich, Switzerland. Factors related to biogenic and wood-burning-derived SOAs are quantified, as well as POA sources such as wood burning, cigarette smoke, cooking, and traffic. The retrieved EESI-TOF factor-dependent sensitivities are consistent with both laboratory measurements of SOA from model precursors and bulk sensitivity parameterisations based on ion chemical formulae. The cPMF analysis shows that, with the standalone EESI-TOF PMF, in which factor-dependent sensitivities are not accounted for, some factors are significantly under- or overestimated. For example, when factor-dependent sensitivities are not considered in the winter dataset, the SOA fraction is underestimated by ∼25 % due to the high EESI-TOF sensitivity to components of primary biomass burning such as levoglucosan. In the summer dataset, where both SOA and total OA are dominated by monoterpene oxidation products, the uncorrected EESI-TOF underestimates the fraction of daytime SOA relative to nighttime SOA (in which organonitrates and less oxygenated C x H y O z molecules are enhanced). Although applied here to an AMS and EESI-TOF pairing, cPMF is suitable for the general case of a multi-instrument dataset, thereby providing a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment. [ABSTRACT FROM AUTHOR]

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

In recent years, intense haze events in megacities such as Beijing have received significant study. Although secondary organic aerosol (SOA) has been identified as a major contributor to such events, knowledge of its sources and formation mechanisms remains uncertain. We investigate this question through the first field deployment of the extractive electrospray ionisation time-of-flight mass spectrometer (EESI-TOF-MS) in Beijing, together with an Aerodyne long time-of-flight aerosol mass spectrometer (L-TOF AMS). Measurements were performed during autumn and winter 2017, capturing the transition from non-heating to heating seasons. Source apportionment resolved four factors related to primary organic aerosols (traffic, cooking, biomass burning, and coal combustion), as well as four related to secondary organic aerosol (SOA). Of the SOA factors, two were related to solid fuel combustion (SFC), one to SOA generated from aqueous chemistry, and one to mixed/indeterminate sources. The SFC factors were identified from spectral signatures corresponding to aromatic oxidation products, while the aqueous SOA factor was characterised by signatures of small organic acids and diacids, and unusually low CO+/CO2+ fragment ratios measured by the AMS. Solid fuel combustion was the dominant source of SOA during the heating season. However, a comparably intense haze event was also observed in the non-heating season, and was dominated by the aqueous SOA factor. Aqueous chemistry was promoted by the combination of high relative humidity and air masses passing over high NOx regions to the south and east of Beijing, leading to high particulate nitrate. The resulting high liquid water content was highly correlated with the concentration of the aqueous SOA factor. These results highlight the strong compositional variability between different haze events, indicating the need to consider multiple formation pathways and precursor sources to describe SOA during intense haze events in Beijing. [ABSTRACT FROM AUTHOR]

We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France), which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). In total 216 PM2. 5 (particulate matter with an aerodynamic diameter  <  2.5 µm) filter samples were collected over 1 year from August 2011 to July 2012. These filters were used to create 54 composite samples which were analyzed by offline-AMS. The same samples were also analyzed for major water-soluble ions, metals, elemental and organic carbon (EC ∕ OC), and organic markers, including n-alkanes, hopanes, polycyclic aromatic hydrocarbons (PAHs), lignin and cellulose pyrolysis products, and nitrocatechols. The application of positive matrix factorization (PMF) to the water-soluble AMS spectra enabled the extraction of five factors, related to hydrocarbon-like OA (HOA), cooking OA (COA), biomass burning OA (BBOA), oxygenated OA (OOA), and an industry-related OA (INDOA). Seasonal trends and relative contributions of OA sources were compared with the source apportionment of OA spectra collected from the AMS field deployment at the same station but in different years and for shorter monitoring periods (February 2011 and July 2008). Online- and offline-AMS source apportionment revealed comparable seasonal contribution of the different OA sources. Results revealed that BBOA was the dominant source during winter, representing on average 48 % of the OA, while during summer the main OA component was OOA (63 % of OA mass on average). HOA related to traffic emissions contributed on a yearly average 17 % to the OA mass, while COA was a minor source contributing 4 %. The contribution of INDOA was enhanced during winter (17 % during winter and 11 % during summer), consistent with an increased contribution from light alkanes, light PAHs (fluoranthene, pyrene, phenanthrene), and selenium, which is commonly considered as a unique coal combustion and coke production marker. Online- and offline-AMS source apportionments revealed evolving levoglucosan : BBOA ratios, which were higher during late autumn and March. A similar seasonality was observed in the ratios of cellulose combustion markers to lignin combustion markers, highlighting the contribution from cellulose-rich biomass combustion, possibly related to agricultural activities. [ABSTRACT FROM AUTHOR]