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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 Ox (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.

Atmospheric aerosol particles are a complex combination of primary emitted sources (biogenic and anthropogenic) and secondary aerosol resulting from the aging processes such as condensation, coagulation, and cloud processing. To better understand their sources, investigations have been focused on source identification in urban areas in the past, while 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. Moreover, long-term measurements can help to study the potential temporal changes in the sources. Here, the chemical composition and organic aerosol sources of submicron aerosol particles were investigated at the Central European rural-background research station, Melpitz, using a one yearlong dataset determined by an aerosol chemical speciation monitor (ACSM) and a multi-angle absorption photometer (MAAP) from September 2016 to August 2017. Melpitz represents due to its location the Central European aerosol. It is an ideal location to investigate the impact of long-range transport, since the location is influenced by less polluted air masses from westerly directions and more polluted continental air masses from Eastern Europe. The organic aerosol (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 sulphate (15 % and 20 %) and nitrate (24 % and 11 %). The OA source identification was performed using rolling positive matrix factorisation (PMF) approach to account for the potential temporal changes in the source profile (SoFi Pro). It was possible to split OA into five-factors with a distinct temporal variability and mass spectral signature. Three were associated to 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/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 multi-linear 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 show that during both winter and summer time, PM1 (PM with aerodynamic diameter smaller than 1 µm) air masses with eastern influence was always associated with the highest mass concentration and the highest coal combustion fraction. Since during winter time, CCOA is a combination of domestic heating and power plants emissions, the summer contribution of CCOA emphasises the critical importance of coal power plants emissions to rural background aerosols and its impact on air quality, through long-range transportation.

Particulate matter is usually regarded as the dominant pollutant in Tehran megacity in Iran. However, the number of ozone exceedance days significantly increased in recent years. This study analyzes simultaneous measurements of O3 and NOx (NO+NO2) concentrations to improve our understanding of ozone evolution during the summers of 2017 to 2019. The k-means clustering technique was used to select five representative air quality monitoring sites in Tehran to capture O3 and NOx concentrations' variability. The findings show that all of the investigated sites failed to meet the ozone non-attainment criterion. The ozone weekend effect is seen in the study of weekday/weekend differences in 2017 and 2018, but not in 2019, which can be due to the shift in the ozone production regime. The summer mean variation analysis can also be used to deduce this regime change. In 2017, the O3 and NO2 summer mean variations suggest a holdback in the NO2 upward trend and a reversal in the O3 downward trend that had been in place since 2012. Air mass back trajectory clustering reveals that east and north-east air mass clusters have the most significant impact on Tehran's O3 pollution and the highest regional contribution to OX. The study of OX against NOx shows that the regional contribution to OX increased from 2017 to 2018 and then decreased in 2019; however, the local contribution is the opposite. The diurnal analysis of the regional and local contributions to OX indicated that OX in Tehran might be primarily affected by pollutants from a short distance. The findings reveal critical changes in the behavior of O3 in recent years, indicating that decision-makers in Tehran should reconsider air pollution control measures.

The first excited state of molecular oxygen is singlet-state oxygen (

Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected "true"values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling-seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach., Acknowledgements IDAEA-CSIC is a Centre of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). The authors gratefully acknowledge the Romanian National Air Quality Monitoring Network (NAQMN, https://www.calitateaer.ro/public/home-page/?__locale=ro, last access: September 2022) for providing NOx data. Financial support This research has been supported by the Generalitat de Catalunya (grant no. AGAUR 2017 SGR41), the European Cooperation in Science and Technology (grant no. COST Action CA16109 COLOSSAL), the Ministerio de Ciencia, Innovación y Universidades (CAIAC, grant no. PID2019-108990RB-I00 and FEDER, grant no. EQC2018-004598-P.), the Horizon 2020, the Ministry of Education and Research, Romania (grant nos. PN-III-P1-1.1-TE-2019-0340 and 18PFE/30.12.2021, 18N/2019), the Agence Nationale de la Recherche (grant no. PIA, ANR-11_LABX-0005-01), the Conseil Régional Hauts-de-France (CLIMIBIO grant), the Ministère de l'Enseignement Supérieur et de la Recherche (CARA grant), the Environmental Protection Agency (AEROSOURCE, grant no. 2016-CCRP-MS-31), the Department of the Environment, Climate and Communications (AC3 network grant), and the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SAMSAM, grant nos. IZCOZ9_177063 and PZPGP2_201992). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based radiocarbon (14C) data, Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) analysis on filter-based chemical speciation data, and PMF analysis on Aerosol Mass Spectrometer (AMS-PMF) or Aerosol Chemical Speciation Monitor (ACSM-PMF) data. These data were collected as part of the APHH-Beijing (Atmospheric Pollution and Human Health in a Chinese Megacity) field observation campaigns from 10th November to 12th December in winter 2016 and from 22nd May to 24th June in summer 2017. 14C analysis revealed the predominant contribution of fossil fuel combustion to carbonaceous aerosols in winter compared with non-fossil fuel sources, which is supported by the results from other methods. An extended Gelencs´er (EG) method incorporating 14C data, as well as the CMB and AMS/ACSM-PMF methods, generated a consistent source apportionment for fossil fuel related primary organic carbon. Coal combustion, traffic and biomass burning POC were comparable for CMB and AMS/ACSM-PMF. There are uncertainties in the EG method when estimating biomass burning and cooking OC. The POC from cooking estimated by different methods was poorly correlated, suggesting a large uncertainty when differentiating this source type. The PM2.5 source apportionment results varied between different methods. Through a comparison and correlation analysis of CMB, PMF and AMS/ACSM-PMF, the CMB method appears to give the most complete and representative source apportionment of Beijing aerosols. Based upon the CMB results, fine aerosols in Beijing were mainly secondary inorganic ion formation, secondary organic aerosol formation, primary coal combustion and from biomass burning emissions.

A year-long offline based study was performed at five sites of Indo-Gangetic plain to get the spatio-temporal variation in elemental carbon (EC), organic carbon (OC), water-soluble organic carbon (WSOC) and secondary organic aerosol (SOA) in PM2.5 fraction. OC constitutes ~70–90% of the total carbon with high water-soluble fraction (60–70%) during winter, except at Hisar. The change in concentration of OC was insignificant during summer, whereas the water-soluble fraction increased by 75–85%. The relatively high OC/EC ratio (7–11) and OC/K+ ratio (10–52) during winter and post-monsoon suggest the dominance of biomass burning from wood fuel and agricultural waste. EC is nearly constant over the seasons at all sites suggesting the dominant presence of traffic-originated EC throughout the year. Interestingly, a low correlation (~0.3) between OC and EC at IITD and IITMD indicates their source from different origins. Exceptionally, the daytime OC/EC ratio was slightly higher than night time during winter at Hisar. However, other sites showed the opposite trend. A significant linear relationship between WSOC and secondary organic carbon suggests dominant contribution from SOA. A paired t-test results indicate much of WSOC is of secondary origin and regional in nature. The secondary fraction contributed 30–60% of OC during winter across all the sites in IGP, whereas during summer it varied between 20 and 40%. SOA estimated by the EC- tracer method has the highest contribution at IITMD (~138 μg/m3) among all the sites and peaked during post-monsoon.

PM2.5 filter sampling and components measurement were conducted in autumn and winter from 2014 to 2015 at a suburban site (referred herein as "LLH site") located in the southwest of Beijing. The offline aerosol mass spectrometry (offline-AMS) analysis and positive matrix factorization (PMF) were applied for measurement and source apportionment of water-soluble organic aerosol (WSOA). Organic aerosol (OA) always dominated PM2.5 during the sampling period, especially in winter. WSOA pollution was serious during the polluted period both in autumn (31.1 µg/m3) and winter (31.9 µg/m3), while WSOA accounted for 54.4% of OA during the polluted period in autumn, much more than that (21.3%) in winter. The oxidation degree of WSOA at LLH site was at a high level (oxygen-to-carbon ratio, O/C=0.91) and secondary organic aerosol (SOA) contributed more mass ratio of WSOA than primary organic aerosol (POA) during the whole observation period. In winter, coal combustion OA (CCOA) was a stable source of OA and on average accounted for 25.1% of WSOA. In autumn, biomass burning OA (BBOA) from household combustion contributed 38.3% of WSOA during polluted period. In addition to oxygenated OA (OOA), aqueous-oxygenated OA (aq-OOA) was identified as an important factor of SOA. During heavy pollution period, the mass proportion of aq-OOA to WSOA increased significantly, implying the significant SOA formation through aqueous-phase process. The result of this study highlights the concentration on controlling the residential coal and biomass burning, as well as the research needs on aqueous chemistry in OA formation.

The oxidative potential (OP) of ambient particulate matter (PM) is a metric commonly used to link the aerosol exposure to its adverse health effects. In this study, we report the first-ever real-ti...

Organic aerosols in the Arctic are predominantly fuelled by anthropogenic sources in winter and natural sources in summer, according to observations from eight sites across the Arctic Aerosols play an important yet uncertain role in modulating the radiation balance of the sensitive Arctic atmosphere. Organic aerosol is one of the most abundant, yet least understood, fractions of the Arctic aerosol mass. Here we use data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol. We show that during winter, the organic aerosol in the Arctic is dominated by anthropogenic emissions, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution. In summer, the decreasing anthropogenic pollution is replaced by natural emissions. These include marine secondary, biogenic secondary and primary biological emissions, which have the potential to be important to Arctic climate by modifying the cloud condensation nuclei properties and acting as ice-nucleating particles. Their source strength or atmospheric processing is sensitive to nutrient availability, solar radiation, temperature and snow cover. Our results provide a comprehensive understanding of the current pan-Arctic organic aerosol, which can be used to support modelling efforts that aim to quantify the climate impacts of emissions in this sensitive region.

In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winters. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role, but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/2019, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and 2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 local time). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA dominated factors were related to the total AMS SOA (i.e., MO-OOA + LO-OOA) by multi-linear regression (MLR). Aromatic SOA was the major SOA component during the day-time, with 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during night-time. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during day-time and 36.1 % of total SOA mass (11.2 % of total OA) during night-time. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass ( 11.7 % and 8.5 % of total OA mass) during day-time respectively and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass) during night-time, respectively. A simple dilution/partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed day-time concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted VOCs. In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the night-time high concentrations are caused by POA emissions led by traffic and biomass burning, and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the day-time suggests an increased OA toxicity and health-related consequences for the general public.

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.

Understanding the sources of light-absorbing organic (brown) carbon (BrC) and its interaction with black carbon (BC) and other non-refractory particulate matter (NR-PM) fractions is important for reducing uncertainties in the aerosol direct radiative forcing. In this study, we combine multiple filter-based techniques to achieve long-term, spectrally resolved, source- and species-specific atmospheric absorption closure. We determine the mass absorption efficiency (MAE) in dilute bulk solutions at 370 nm to be equal to 1.4 m2 g−1 for fresh biomass smoke, 0.7 m2 g−1 for winter-oxygenated organic aerosol (OA), and 0.13 m2 g−1 for other less absorbing OA. We apply Mie calculations to estimate the contributions of these fractions to total aerosol absorption. While enhanced absorption in the near-UV has been traditionally attributed to primary biomass smoke, here we show that anthropogenic oxygenated OA may be equally important for BrC absorption during winter, especially at an urban background site. We demonstrate that insoluble tar balls are negligible in residential biomass burning atmospheric samples of this study and thus could attribute the totality of the NR-PM absorption at shorter wavelengths to methanol-extractable BrC. As for BC, we show that the mass absorption cross-section (MAC) of this fraction is independent of its source, while we observe evidence for a filter-based lensing effect associated with the presence of NR-PM components. We find that bare BC has a MAC of 6.3 m2 g−1 at 660 nm and an absorption Ångström exponent of 0.93 ± 0.16, while in the presence of coatings its absorption is enhanced by a factor of ∼ 1.4. Based on Mie calculations of closure between observed and predicted total light absorption, we provide an indication for a suppression of the filter-based lensing effect by BrC. The total absorption reduction remains modest, ∼ 10 %–20 % at 370 nm, and is restricted to shorter wavelengths, where BrC absorption is significant. Overall, our results allow an assessment of the relative importance of the different aerosol fractions to the total absorption for aerosols from a wide range of sources and atmospheric ages. When integrated with the solar spectrum at 300–900 nm, bare BC is found to contribute around two-thirds of the solar radiation absorption by total carbonaceous aerosols, amplified by the filter-based lensing effect (with an interquartile range, IQR, of 8 %–27 %), while the IQR of the contributions by particulate BrC is 6 %–13 % (13 %–20 % at the rural site during winter). Future studies that will directly benefit from these results include (a) optical modelling aiming at understanding the absorption profiles of a complex aerosol composed of BrC, BC and lensing-inducing coatings; (b) source apportionment aiming at understanding the sources of BC and BrC from the aerosol absorption profiles; (c) global modelling aiming at quantifying the most important aerosol absorbers., Atmospheric Chemistry and Physics, 21 (17), ISSN:1680-7375, ISSN:1680-7367

Aerosol mass spectrometry (AMS) and mid-infrared spectroscopy (MIR) are two analytical methods for characterizing the chemical composition of organic matter (OM). While AMS provides high-temporal-resolution bulk measurements, the extensive fragmentation during the electron ionization makes the characterization of OM components limited. The analysis of aerosols collected on polytetrafluoroethylene (PTFE) filters using MIR, on the other hand, provides functional group information with reduced sample alteration but results in a relatively low temporal resolution. In this work, we compared and combined MIR and AMS measurements for several environmental chamber experiments of combustion-related aerosols to achieve a better understanding of the AMS spectra and the OM chemical evolution with aging. Fresh emissions of wood and coal burning were injected into an environmental simulation chamber and aged with hydroxyl and nitrate radicals. A high-resolution time-of-flight AMS measured the bulk chemical composition of fine OM. Fine aerosols were also sampled on PTFE filters before and after aging for the offline MIR analysis. After comparing AMS and MIR bulk measurements, we used multivariate statistics to identify the functional groups associated the most with the AMS OM for different aerosol sources and oxidants. We also identified the key fragment ions resulting from molecules containing each functional group for the complex OM generated from biomass and fossil fuel combustion. Finally, we developed a statistical model that enables the estimation of the high-time-resolution functional group composition of OM using collocated AMS and MIR measurements. AMS spectra can be used to interpolate the functional group measurements by MIR using this approach. The latter allows us to better understand the evolution of OM during the aging process.

Cooking is recognized as an important source of particulate pollution in indoor and outdoor environments. We conducted more than 100 individual experiments to characterize the particulate and non‐methane organic gas emissions from various cooking processes, their reaction rates, and their secondary organic aerosol yields. We used this emission data to develop a box model, for simulating the cooking emission concentrations in a typical European home and the indoor gas‐phase reactions leading to secondary organic aerosol production. Our results suggest that about half of the indoor primary organic aerosol emission rates can be explained by cooking. Emission rates of larger and unsaturated aldehydes likely are dominated by cooking while the emission rates of terpenes are negligible. We found that cooking dominates the particulate and gas‐phase air pollution in non‐smoking European households exceeding 1000 μg m−3. While frying processes are the main driver of aldehyde emissions, terpenes are mostly emitted due to the use of condiments. The secondary aerosol production is negligible with around 2 μg m−3. Our results further show that ambient cooking organic aerosol concentrations can only be explained by super‐polluters like restaurants. The model offers a comprehensive framework for identifying the main parameters controlling indoor gas‐ and particle‐phase concentrations.

This study aims at testing the effectiveness of Positive Matrix Factorization in characterizing groundwater and surface water quality, in terms of identifying main hydrochemical features and processes (natural and anthropogenic) that govern them. This method is applied in a hydro-system featured by a strong interrelation between groundwater and surface water and highly impacted by agricultural activities. Therefore, a holistic approach considering groundwater together with the surface water bodies, consisting in lake, several rivers and springs, was used. Multivariate statistical analysis, in particular Factor Analysis, has been proved to be effective in elaborating and interpreting water quality data highlighting the information carried within them, but it presents some limitations: it does not consider data uncertainty and it groups variables which are correlated positively and negatively. Moreover, in some cases the resulting factors are not clearly interpretable, describing each one various overlapping features/processes. Here, Positive Matrix Factorization is applied to groundwater and surface water quality data, and the results are compared to those obtained through a Factor Analysis in terms of both factor profiles and their spatial distribution through a GIS approach. Results of isotopes analysis are used to validate PMF output and support interpretation. Positive Matrix Factorization allows to consider data uncertainty and the solution respects two positivity constraints, based on the concept of chemical mass balance, which leads to a more environmentally interpretable solution. Results show that Positive Matrix Factorization identifies five different factors reflecting main features and natural and anthropogenic processes affecting the study area: 1) surface water used for irrigation, 2) groundwater subjected to reducing processes at advanced stages, 3) groundwater subjected to reducing processes at early stages, 4) groundwater residence time and 5) the effects of the agricultural land use on both groundwater and surface water. Positive Matrix Factorization leads to a more detailed understanding of the studied system as compared to Factor Analysis which identifies only three factors with overlapping information. Based on the results of this study, Positive Matrix Factorization could be a useful technique to perform groundwater and surface water quality characterization and to reach a deeper understanding of the phenomena that govern water chemistry.

Real-time, in situ molecular composition measurements of the organic fraction of fine particulate matter (PM2.5) remain challenging, hindering a full understanding of the climate impacts and health effects of PM2.5. In particular, the thermal decomposition and ionization-induced fragmentation affecting current techniques has limited a detailed investigation of secondary organic aerosol (SOA), which typically dominates OA. Here we deploy a novel extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF-MS) during winter 2017 in downtown Zurich, Switzerland, which overcomes these limitations, together with an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-TOF-AMS) and supporting instrumentation. Positive matrix factorization (PMF) implemented within the Multilinear Engine (ME-2) program was applied to the EESI-TOF-MS data to quantify the primary and secondary contributions to OA. An 11-factor solution was selected as the best representation of the data, including five primary and six secondary factors. Primary factors showed influence from cooking, cigarette smoke, biomass burning (two factors) and a special local unknown event occurred only during two nights. Secondary factors were affected by biomass burning (three factors, distinguished by temperature and/or wind direction), organonitrates, monoterpene oxidation, and undetermined regional processing, in particular the contributions of wood combustion. While the AMS attributed slightly over half the OA mass to SOA but did not identify its source, the EESI-TOF-MS showed that most (>70 %) of the SOA was derived from biomass burning. Together with significant contributions from less aged biomass burning factors identified by both AMS and EESI-TOF-MS, this firmly establishes biomass burning as the single most important contributor to OA mass at this site during winter. High correlation was obtained between EESI-TOF-MS and AMS PMF factors where specific analogues existed, as well as between total signal and POA–SOA apportionment. This suggests the EESI-TOF-MS apportionment in the current study can be approximately taken at face value, despite ion-by-ion differences in relative sensitivity. The apportionment of specific ions measured by the EESI-TOF-MS (e.g., levoglucosan, nitrocatechol, and selected organic acids) and utilization of a cluster analysis-based approach to identify key marker ions for the EESI-TOF-MS factors are investigated. The interpretability of the EESI-TOF-MS results and improved source separation relative to the AMS within this pilot campaign validate the EESI-TOF-MS as a promising approach to source apportionment and atmospheric composition research.

The main sources of particulate emissions from engines are fuel and lubricating oil. In this study, particles emitted by a medium speed diesel engine for locomotive use were characterized chemicall...

The NO3 radical represents a significant night-time oxidant present in or downstream of polluted environments. There are studies that investigated the formation of secondary organic aerosol (SOA) from NO3 radicals focusing on yields, general composition, and hydrolysis of organonitrates. However, there is limited knowledge about how the composition of NO3-derived SOA evolves as a result of particle phase reactions. Here, SOA was formed from the reaction of α-pinene with NO3 radicals generated from N2O5, and the resulting SOA aged in the absence of external stimuli. The initial composition of NO3-derived α-pinene SOA was slightly dependent upon the concentration of N2O5 injected (excess of NO3 or excess of α-pinene), but was largely dominated by dimer dinitrates (C20H32N2O8-13). Oxidation reactions (e.g. C20H32N2O8 C20H32N2O9 C20H32N2O10 etc...) accounted for 60–70 % of the particle phase reactions observed. Fragmentation reactions and dimer degradation pathways made up the remainder of the particle-phase processes occurring. The exact oxidant is not known, though suggestions are offered (e.g. N2O5, organic peroxides, or peroxy-nitrates). Hydrolysis of −ONO2 functional groups was not an important loss term during dark aging under the relative humidity conditions of our experiments (58–62 %), and changes in the bulk organonitrate composition were likely driven by evaporation of highly nitrogenated molecules. Overall, 25–30 % of the particle-phase composition changes as a function of particle-phase reactions during dark aging representing an important atmospheric aging pathway.

Smog chamber experiments were conducted to characterize the light absorption of brown carbon (BrC) from primary and photochemically aged coal combustion emissions. Light absorption was measured by the UV-visible spectrophotometric analysis of water and methanol extracts of filter samples. The single-scattering albedo at 450 nm was 0.73 ± 0.10 for primary emissions and 0.75 ± 0.13 for aged emissions. The light absorption coefficient at 365 nm of methanol extracts was higher than that of water extracts by a factor of 10 for primary emissions and a factor of 7 for aged emissions. This suggests that the majority of BrC is water-insoluble even after aging. The mass absorption efficiency of this BrC (MAE365) for primary OA (POA) was dependent on combustion conditions, with an average of 0.84 ± 0.54 m2 g-1, which was significantly higher than that for aged OA (0.24 ± 0.18 m2 g-1). Secondary OA (SOA) dominated aged OA and the decreased MAE365 after aging indicates that SOA is less light absorbing than POA and/or that BrC is bleached (oxidized) with aging. The estimated MAE365 of SOA (0.14 ± 0.08 m2 g-1) was much lower than that of POA. A comparison of MAE365 of residential coal combustion with other anthropogenic sources suggests that residential coal combustion emissions are among the strongest absorbing BrC organics.

In the present work, we conducted experiments of secondary organic aerosol (SOA) formation from urban lifestyle sources (cooking and vehicle) 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 greater impact on aged COA mass spectra than oxidation condition. However, the oxidation conditions affect the aged HOA spectra more significantly than vehicle operation 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 typical lifestyle sources. These mass spectra are used as source constraints in a multilinear engine (ME-2) model to apportion the OA sources in the atmosphere. Comparing with the traditional ambient PMF results, the improved ME-2 model can better quantify the contribution of POA and SOA from life-style 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.

Krakow is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been done on characterization of ambient aerosols, there is a lack of online and long-term measurements of non-refractory aerosols. Our measurements at AGH University provide 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 aerosols 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 of the source profiles can be captured. The uncertainties of 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 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 primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of 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. The highest contributions are observed during wintertime as a result of residential heating. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contribution of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively.

Despite decades of declining air pollution, urban U.S. areas are still affected by summertime ozone and wintertime particulate matter exceedance events. Volatile organic compounds (VOCs) are known precursors of secondary organic aerosol (SOA) and photochemically produced ozone. Urban VOC emission sources, including on-road transportation emissions, have decreased significantly over the past few decades through successful regulatory measures. These drastic reductions in VOC emissions have led to a change in the distribution of urban emissions and noncombustion sources of VOCs such as those from volatile chemical products (VCPs), which now account for a higher fraction of the urban VOC burden. Given this shift in emission sources, it is essential to quantify the relative contribution of VCP and mobile source emissions to urban pollution. Herein, ground site and mobile laboratory measurements of VOCs were performed. Two ground site locations with different population densities, Boulder, CO, and New York City (NYC), NY, were chosen in order to evaluate the influence of VCPs in cities with varying mixtures of VCPs and mobile source emissions. Positive matrix factorization was used to attribute hundreds of compounds to mobile- and VCP-dominated sources. VCP-dominated emissions contributed to 42 and 78% of anthropogenic VOC emissions for Boulder and NYC, respectively, while mobile source emissions contributed 58 and 22%. Apportioned VOC emissions were compared to those estimated from the Fuel-based Inventory of Vehicle Emissions and VCPs and agreed to within 25% for the bulk comparison and within 30% for more than half of individual compounds. The evaluated inventory was extended to other U.S. cities and it suggests that 50 to 80% of emissions, reactivity, and the SOA-forming potential of urban anthropogenic VOCs are associated with VCP-dominated sources, demonstrating their important role in urban U.S. air quality.

Two fractions of suspended particulate matter (PM1 and PM10) were collected on daily basis in the urban atmosphere of Krakow, southern Poland, during one-year period (April 2018 - April 2019). The following compounds were examined: elemental carbon (EC), organic carbon (OC), carbohydrates (among them levoglucosan – a recognized biomass tracer), as well as ions (Li+, Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO2-, Br-. NO32-, PO43-, SO42-). Thermal-optical analysis with a Sunset carbon analyzer, (Sunset Lab. Inc.) was used to obtain information about organic and elemental carbon concentration, while HPAE-PAD Dionex ICS 3000 system was employed to determine the concentration of 14 carbohydrates. Concentration of ions was analysed using isocratic ion chromatography on an ICS-1100 instrument (Thermo Scientific).Distinct seasonality of chemical composition of PM1 and PM10 fraction was observed. Levoglucosan concentration ranged from 0.01 ug/m3 to 0.90 ug/m3 (PM1 fraction) and from 0.01 to ug/m3 to 1.95 ug/m3 (PM10 fraction) during the analysed period. Arabitol and Mannitol were detected only in PM10 fraction and ranged from 0.01 ug/m3 and 0.02 ug/m3, during winter season and to 0.15 ug/m3 and 0.10 ug/m3, respectively, during summer season. Significant seasonal differences were also found for ion concentrations: from 0.49 μg/m3 (SO42-), 0.15 μg/m3 (NO3-) and 0.05 μg/m3 (NH4+) during summer season, to be compared with 11.16 μg/m3 (SO42-), 9.30 μg/m3 (NO3-), 9.25 μg/m3 (NH4+) for winter season. The concentration of organic and elemental carbon in PM10 fraction ranged from 2.0 μg/m3 to 48.9 μg/m3 (OC) and from 0.3 μg/m3 to 10.0 μg/m3 (EC), to be compared with 1.4 μg/m3 to 18.1 μg/m3 (OC) and 0.2 μg/m3 to 4.4 μg/m3 (EC) for PM1 fraction. ACKNOWLEDGEMENTSThe presented work was funded by Polish National Science Centre (project No. 2019/33/N/ST10/02925) as well as COST Action COLOSSAL (CA16109) of EU. Work of AS and PF have been partly supported by the EU Project POWR.03.02.00-00-I004/16. Analytical infrastructure of AGH Center of Energy in Krakow was employed in analyses of selected ions.

International audience; Long-term and continuous measurements of aerosol chemical composition is essential to improve our understanding of the formation and transformation of aerosol particles in the atmosphere. Thanks to the recent developments of aerosol mass spectrometry, notably with the Aerosol Chemical Speciation Monitor (ACSM, Aerodyne; Fröhlich et al., 2013; Ng et al., 2011), this information can be acquired over long periods of time with minimal intervention from the user. The ACSM is a robust tool that measures aerosol chemical properties of the aerosol with time resolutions ranging from 10 to 30 min. Global long-term ACSM data sets have recently been presented in the literature, including a 6-year study near Paris (France; Petit et al., 2015; Zhang et al., 2019), a 2-year study in the megacity of Beijing (China; Sun et al., 2018), and a 5-year study from Leipzig (Germany; Poulain et al., 2020). The measurements within Europe are mostly being performed within the framework of the ACTRIS infrastructure (Aerosols, Clouds, and Trace gases Research InfraStructure), and a growing database of these measurements is available via the EBAS database (http://ebas.nilu. no/). Pluri-annuel and multi seasonal studies provide an opportunity to study how aerosol particles concentrations and chemical signature evolves over time in response to different airmass sources and atmospheric changes. This information is useful for understanding transport and aging patterns and can also be used for the validation of atmospheric models. Similar to worldwide measurements at low altitudes (Jimenez et al., 2009; Zhang et al., 2007), organic species also dominate the PM1 mass concentrations at high altitudes (Zhou et al., 2019). Fröhlich et al. (2015) at the Jungfraujoch station (JFJ, 3,580 m a.s.l), showed that organics were the dominant species, making

The European air quality in 2010 was simulated by the regional air quality model CAMx in two different projects: Eurodelta-Trends (EDT) and PSI-Project. We used the same model version CAMx v6.50 and the same parameterization in both projects but with different domain resolution and input data. In this study, we investigated (i) how different are the results for ozone, PM2.5 and its components and (ii) which parameter/input is more critical for each pollutant. Our analyses suggested that the differences mainly originated from the boundary conditions, biogenic emissions and the vertical distribution of anthropogenic emissions. The most sensitive species to inputs were ozone and secondary organic aerosols (SOA). The difference in ozone concentrations was mainly due to the difference in boundary conditions. On the other hand, the difference in the annual PM2.5 concentrations originated mainly from SOA, due to different biogenic emissions used in the two projects. Concentrations of secondary inorganic aerosols (SIA) were comparable with small differences due to the different resolutions and vertical distribution of emissions. Although their generation was not the same, the meteorological data were similar in both projects and effects of small differences were not significant for the annual concentrations of pollutants.

Characteristics and sources of volatile organic compounds (VOCs) were investigated with highly time-resolved measurements by a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) at an urban site in Beijing in winter 2017. During the measurement period, high mixing ratios of VOCs (48.9 ppbv) and trace gases were observed, with alternating episodes of strong haze pollution and clean air. Ten VOC families showed clear dependence on the VOC concentration. Aromatics increased the most during haze, with significantly elevated benzene concentration at high VOC concentration, while CxHyO3 and CxHy increased the least. The positive matrix factorization (PMF) receptor model was applied to the VOC mass spectra, yielding four major VOC factors: traffic emissions (21.0%), solid fuel combustion (SFC, 24.4%), and two oxygenated VOC (OVOC) factors (32.3% and 22.3%). Traffic and solid fuel combustion were dominant during the periods of high total VOC concentration, while the OVOC1 fraction was reduced. Comparisons with organic aerosol (OA) sources showed increased oxygenated organic aerosol (OOA) concentration during high VOC concentration periods, indicating the importance of OVOCs to secondary organic aerosol formation. Furthermore, trajectory analysis showed that most of the clean days were associated with northerly winds with high ratios of OVOC1. In contrast, the haze periods were not only due to high primary emissions under stagnant conditions, but also influenced by air masses from a more regional scale.

Aerosol particles negatively affect human health while also having climatic relevance due to, for example, their ability to act as cloud condensation nuclei. Ultrafine particles (diameter Dp < 100 nm) typically comprise the largest fraction of the total number concentration, however, their chemical characterization is difficult because of their low mass. Using an extractive electrospray time-of-flight mass spectrometer (EESI-TOF), we characterize the molecular composition of freshly nucleated particles from naphthalene and β-caryophyllene oxidation products at the CLOUD chamber at CERN. We perform a detailed intercomparison of the organic aerosol chemical composition measured by the EESI-TOF and an iodide adduct chemical ionization mass spectrometer equipped with a filter inlet for gases and aerosols (FIGAERO-I-CIMS). We also use an aerosol growth model based on the condensation of organic vapors to show that the chemical composition measured by the EESI-TOF is consistent with the expected condensed oxidation products. This agreement could be further improved by constraining the EESI-TOF compound-specific sensitivity or considering condensed-phase processes. Our results show that the EESI-TOF can obtain the chemical composition of particles as small as 20 nm in diameter with mass loadings as low as hundreds of ng m−3 in real time. This was until now difficult to achieve, as other online instruments are often limited by size cutoffs, ionization/thermal fragmentation and/or semi-continuous sampling. Using real-time simultaneous gas- and particle-phase data, we discuss the condensation of naphthalene oxidation products on a molecular level., Using real-time simultaneous gas- and particle-phase data, the condensation of naphthalene and β-caryophyllene oxidation products on a molecular level is discussed.

Organic aerosols (OA) contribute to 20–90% of the particulate matter (PM) concentration worldwide. To investigate the effects of OA schemes on PM modeling, we conducted whole-year (2010) simulations in Europe using the regional air quality model CAMx v6.50 with three different OA schemes: (1) an updated version of the traditional Odum 2-product model SOAP2.1, (2) the standard volatility basis set (VBS) algorithm, and (3) a modified VBS scheme which applies 3 times of POA emissions to offset the influence of missing semi-volatile organic compound (SVOC) emissions and enables aging of secondary condensable gases from biomass burning (referred as VBSNEW). The modeled OA concentration by SOAP was significantly higher than OA by VBS over land especially in the eastern Europe, while VBS led to higher OA only over the Mediterranean sea. The higher OA–SOAP mainly came from the primary organic aerosol (POA), which was 0.4 µg m−3 higher than POA–VBS on average. However, the SOA–VBS was higher than SOA–SOAP in most of the areas except for the northeastern Europe, where the modeled OA concentration was strongly influenced by the boundary conditions. The VBSNEW increased the domain average OA by 26% and 63% compared to SOAP and VBS, respectively. Both POA and SOA were increased by VBSNEW, especially in winter when biomass burning is the dominant OA source. Comparison with observed PM2.5 in 432 AIRBASE stations in Europe showed that VBSNEW led to lowest mean bias (MB) and root-mean-square error (RMSE), which reduced MB by 1.3 and 0.7 μg m−3 compared to VBS and SOAP.