CCN closure study: Effects of aerosol chemical composition and mixing state

TL;DR: In this article, the effects of chemical composition (bulk and size resolved) and mixing state (internal and external) on CCN activity of aerosols were investigated during the winter season in Kanpur.

Abstract: This study presents a detailed cloud condensation nuclei (CCN) closure study that investigates the effects of chemical composition (bulk and size resolved) and mixing state (internal and external) on CCN activity of aerosols. Measurements of the chemical composition, aerosol size distribution, total number concentration, and CCN concentration at supersaturation (SS = 0.2–1.0%) were performed during the winter season in Kanpur, India. Among the two cases considered here, better closure results are obtained for case 1 (low total aerosol loading, 49.54 ± 26.42 μg m−3, and high O:C ratio, 0.61 ± 0.07) compared to case 2 (high total aerosol loading, 101.05 ± 18.73 μg m−3, and low O:C ratio, 0.42 ± 0.06), with a maximum reduction of 3–81% in CCN overprediction for all depleted SS values (0.18–0.60%). Including the assumption that less volatile oxidized organic aerosols represent the soluble organic fraction reduced the overprediction to at most 40% and 129% in the internal and external mixing scenarios, respectively. At higher depleted SS values (0.34–0.60%), size-resolved chemical composition with an internal mixing state performed well in CCN closure among all organic solubility scenarios. However, at a lower depleted SS value (0.18%), closure is found to be more sensitive to both the chemical composition and mixing state of aerosols. At higher SS values, information on the solubility of organics and size-resolved chemical composition is required for accurate CCN predictions, whereas at lower SS values, information on the mixing state in addition to the solubility of organics and size-resolved chemical composition is required. Overall, κtotal values are observed to be independent of the O:C ratio [κtotal = (0.36 ± 0.01) × O:C − (0.03 ± 0.01)] in the range of 0.2

TL;DR: In this article, the mean hygroscopicity parameters (κs) of 50, 100, 150, 200, and 250 nm particles were respectively 0.16, 0.19, p.07 and 0.10, showing an increasing trend with increasing particle size.

Abstract: . Simultaneous measurements of particle number size distribution, particle hygroscopic properties, and size-resolved chemical composition were made during the summer of 2014 in Beijing, China. During the measurement period, the mean hygroscopicity parameters (κs) of 50, 100, 150, 200, and 250 nm particles were respectively 0.16 p 0.07, 0.19 p 0.06, 0.22 p 0.06, 0.26 p 0.07, and 0.28 p 0.10, showing an increasing trend with increasing particle size. Such size dependency of particle hygroscopicity was similar to that of the inorganic mass fraction in PM1. The hydrophilic mode (hygroscopic growth factor, HGF > 1.2) was more prominent in growth factor probability density distributions and its dominance of hydrophilic mode became more pronounced with increasing particle size. When PM2.5 mass concentration was greater than 50 μg m−3, the fractions of the hydrophilic mode for 150, 250, and 350 nm particles increased towards 1 as PM2.5 mass concentration increased. This indicates that aged particles dominated during severe pollution periods in the atmosphere of Beijing. Particle hygroscopic growth can be well predicted using high-time-resolution size-resolved chemical composition derived from aerosol mass spectrometer (AMS) measurements using the Zdanovskii–Stokes–Robinson (ZSR) mixing rule. The organic hygroscopicity parameter (κorg) showed a positive correlation with the oxygen to carbon ratio. During the new particle formation event associated with strongly active photochemistry, the hygroscopic growth factor or κ of newly formed particles is greater than for particles with the same sizes not during new particle formation (NPF) periods. A quick transformation from external mixture to internal mixture for pre-existing particles (for example, 250 nm particles) was observed. Such transformations may modify the state of the mixture of pre-existing particles and thus modify properties such as the light absorption coefficient and cloud condensation nuclei activation.

TL;DR: In this paper, the effects of NO x and SO 2 on secondary organic aerosol (SOA) formation from photooxidation of α-pinene and limonene at ≥ 0.05 to 15.5ppb were investigated.

Abstract: . Anthropogenic emissions such as NO x and SO 2 influence the biogenic secondary organic aerosol (SOA) formation, but detailed mechanisms and effects are still elusive. We studied the effects of NO x and SO 2 on the SOA formation from the photooxidation of α -pinene and limonene at ambient relevant NO x and SO 2 concentrations (NO x : 2 : < 0.05 to 15 ppb). In these experiments, monoterpene oxidation was dominated by OH oxidation. We found that SO 2 induced nucleation and enhanced SOA mass formation. NO x strongly suppressed not only new particle formation but also SOA mass yield. However, in the presence of SO 2 which induced a high number concentration of particles after oxidation to H 2 SO 4 , the suppression of the mass yield of SOA by NO x was completely or partly compensated for. This indicates that the suppression of SOA yield by NO x was largely due to the suppressed new particle formation, leading to a lack of particle surface for the organics to condense on and thus a significant influence of vapor wall loss on SOA mass yield. By compensating for the suppressing effect on nucleation of NO x , SO 2 also compensated for the suppressing effect on SOA yield. Aerosol mass spectrometer data show that increasing NO x enhanced nitrate formation. The majority of the nitrate was organic nitrate (57–77 %), even in low-NO x conditions ( ∼ 1 ppb). Organic nitrate contributed 7–26 % of total organics assuming a molecular weight of 200 g mol −1 . SOA from α -pinene photooxidation at high NO x had a generally lower hydrogen to carbon ratio (H ∕ C), compared to low NO x . The NO x dependence of the chemical composition can be attributed to the NO x dependence of the branching ratio of the RO 2 loss reactions, leading to a lower fraction of organic hydroperoxides and higher fractions of organic nitrates at high NO x . While NO x suppressed new particle formation and SOA mass formation, SO 2 can compensate for such effects, and the combining effect of SO 2 and NO x may have an important influence on SOA formation affected by interactions of biogenic volatile organic compounds (VOCs) with anthropogenic emissions.

TL;DR: Aerosol composition varied largely in different regions, but was overall dominated by organic aerosols (OA, 32-75%), especially in south and southeast Asia due to the impact of biomass burning, and secondary OA was a ubiquitous and dominant aerosol component in all regions.

Abstract: Anthropogenic emissions in Asia have significantly increased during the last two decades; as a result, the induced air pollution and its influences on radiative forcing and public health are becoming increasingly prominent The Aerodyne Aerosol Mass Spectrometer (AMS) has been widely deployed in Asia for real-time characterization of aerosol chemistry In this paper, we review the AMS measurements in Asia, mainly in China, Korea, Japan, and India since 2001 and summarize the key results and findings The mass concentrations of non-refractory submicron aerosol species (NR-PM1) showed large spatial distributions with high mass loadings occurring in India and north and northwest China (602-813 μg m-3), whereas much lower values were observed in Korea, Japan, Singapore and regional background sites (75-151 μg m-3) Aerosol composition varied largely in different regions, but was overall dominated by organic aerosols (OA, 32-75%), especially in south and southeast Asia due to the impact of biomass burning While sulfate and nitrate showed comparable contributions in urban and suburban regions in north China, sulfate dominated inorganic aerosols in south China, Japan and regional background sites Positive matrix factorization analysis identified multiple OA factors from different sources and processes in different atmospheric environments, eg, biomass burning OA in south and southeast Asia and agricultural seasons in China, cooking OA in urban areas, and coal combustion in north China However, secondary OA (SOA) was a ubiquitous and dominant aerosol component in all regions, accounting for 43-78% of OA The formation of different SOA subtypes associated with photochemical production or aqueous-phase/fog processing was widely investigated The roles of primary emissions, secondary production, regional transport, and meteorology on severe haze episodes, and different chemical responses of primary and secondary aerosol species to source emission changes and meteorology were also demonstrated Finally, future prospects of AMS studies on long-term and aircraft measurements, water-soluble OA, the link of OA volatility, oxidation levels, and phase state were discussed

TL;DR: In this article, a detailed time-resolved chemical characterization of ambient nonrefractory submicron aerosols (NR-PM1) was conducted for the first time in India.

Abstract: A detailed time-resolved chemical characterization of ambient nonrefractory submicron aerosols (NR-PM1) was conducted for the first time in India. The measurements were performed during the winter (November 2011 to January 2012) in a heavily polluted city of Kanpur, which is situated in the Indo-Gangetic Plain. Real-time measurements provided new insights into the sources and evolution of organic aerosols (OA) that could not be obtained using previously deployed filter-based measurements at this site. The average NR-PM1 loading was very high (>100 µg/m3) throughout the study, with OA contributing approximately 70% of the total aerosol mass. Source apportionment of the OA using positive matrix factorization revealed large contributions from fresh and aged biomass burning OA throughout the entire study period. A back trajectory analysis showed that the polluted air masses were affected by local sources and distant source regions where the burning of paddy residues occurs annually during winter. Several fog episodes were encountered during the study, and the OA composition varied between foggy and nonfoggy periods, with higher oxygen to carbon (O/C) ratios during the foggy periods. The evolution of OA and their elemental ratios (O:C and H:C) were investigated for the possible effects of fog processing.

TL;DR: In this paper, positive matrix factorization (PMF) was used to identify and interpret the organic aerosol (OA) data from an Aerodyne Aerosol Mass Spectrometer (Q-AMS) collected at the Pittsburgh Air Quality Study (PAQS) in September 2002.

Abstract: . The organic aerosol (OA) dataset from an Aerodyne Aerosol Mass Spectrometer (Q-AMS) collected at the Pittsburgh Air Quality Study (PAQS) in September 2002 was analyzed with Positive Matrix Factorization (PMF). Three components – hydrocarbon-like organic aerosol OA (HOA), a highly-oxygenated OA (OOA-1) that correlates well with sulfate, and a less-oxygenated, semi-volatile OA (OOA-2) that correlates well with nitrate and chloride – are identified and interpreted as primary combustion emissions, aged SOA, and semivolatile, less aged SOA, respectively. The complexity of interpreting the PMF solutions of unit mass resolution (UMR) AMS data is illustrated by a detailed analysis of the solutions as a function of number of components and rotational forcing. A public web-based database of AMS spectra has been created to aid this type of analysis. Realistic synthetic data is also used to characterize the behavior of PMF for choosing the best number of factors, and evaluating the rotations of non-unique solutions. The ambient and synthetic data indicate that the variation of the PMF quality of fit parameter (Q, a normalized chi-squared metric) vs. number of factors in the solution is useful to identify the minimum number of factors, but more detailed analysis and interpretation are needed to choose the best number of factors. The maximum value of the rotational matrix is not useful for determining the best number of factors. In synthetic datasets, factors are "split" into two or more components when solving for more factors than were used in the input. Elements of the "splitting" behavior are observed in solutions of real datasets with several factors. Significant structure remains in the residual of the real dataset after physically-meaningful factors have been assigned and an unrealistic number of factors would be required to explain the remaining variance. This residual structure appears to be due to variability in the spectra of the components (especially OOA-2 in this case), which is likely to be a key limit of the retrievability of components from AMS datasets using PMF and similar methods that need to assume constant component mass spectra. Methods for characterizing and dealing with this variability are needed. Interpretation of PMF factors must be done carefully. Synthetic data indicate that PMF internal diagnostics and similarity to available source component spectra together are not sufficient for identifying factors. It is critical to use correlations between factor and external measurement time series and other criteria to support factor interpretations. True components with

TL;DR: In this paper, the life cycle of dust, sea salt, sulfate, black carbon and particulate organic matter as simulated by sixteen global aerosol models has been analyzed and the differences among the results (model diversities) for sources and sinks, burdens, particle sizes, water uptakes, and spatial dispersals have been established.

Abstract: Simulation results of global aerosol models have been assembled in the framework of the AeroCom intercomparison exercise. In this paper, we analyze the life cycles of dust, sea salt, sulfate, black carbon and particulate organic matter as simulated by sixteen global aerosol models. The differences among the results (model diversities) for sources and sinks, burdens, particle sizes, water uptakes, and spatial dispersals have been established. These diversities have large consequences for the calculated radiative forcing and the aerosol concentrations at the surface. Processes and parameters are identified which deserve further research. The AeroCom all-models-average emissions are dominated by the mass of sea salt (SS), followed by dust (DU), sulfate (SO 4 ), particulate organic matter (POM), and finally black carbon (BC). Interactive parameterizations of the emissions and contrasting particles sizes of SS and DU lead generally to higher diversities of these species, and for total aerosol. The lower diversity of the emissions of the fine aerosols, BC, POM, and SO 4 , is due to the use of similar emission inventories, and does therefore not necessarily indicate a better understanding of their sources. The diversity of SO 4 -sources is mainly caused by the disagreement on depositional loss of precursor gases and on chemical production. The diversities of the emissions are passed on to the burdens, but the latter are also strongly affected by the model-specific treatments of transport and aerosol processes. The burdens of dry masses decrease from largest to smallest: DU, SS, SO 4 , POM, and BC. The all-models-average residence time is shortest for SS with about half a day, followed by SO 4 and DU with four days, and POM and BC with six and seven days, respectively. The wet deposition rate is controlled by the solubility and increases from DU, BC, POM to SO 4 and SS. It is the dominant sink for SO 4 , BC, and POM, and contributes about one third to the total removal of SS and DU species. For SS and DU we find high diversities for the removal rate coefficients and deposition pathways. Models do neither agree on the split between wet and dry deposition, nor on that between sedimentation and other dry deposition processes. We diagnose an extremely high diversity for the uptake of ambient water vapor that influences the particle size and thus the sink rate coefficients. Furthermore, we find little agreement among the model results for the partitioning of wet removal into scavenging by convective and stratiform rain. Large differences exist for aerosol dispersal both in the vertical and in the horizontal direction. In some models, a minimum of total aerosol concentration is simulated at the surface. Aerosol dispersal is most pronounced for SO 4 and BC and lowest for SS. Diversities are higher for meridional than for vertical dispersal, they are similar for the individual species and highest for SS and DU. For these two components we do not find a correlation between vertical and meridional aerosol dispersal. In addition the degree of dispersals of SS and DU is not related to their residence times. SO 4 , BC, and POM, however, show increased meridional dispersal in models with larger vertical dispersal, and dispersal is larger for longer simulated residence times.

TL;DR: In this paper, the authors identify specific compounds that are likely to contribute to the water-soluble fraction by juxtaposing observations regarding the extraction characteristics and the molecular composition of atmospheric particulate organics with compound-specific solubility and condensibility for a wide variety of organics.

Abstract: Although organic compounds typically constitute a substantial fraction of the fine particulate matter (PM) in the atmosphere, their molecular composition remains poorly characterized. This is largely because atmospheric particles contain a myriad of diverse organic compounds, not all of which extract in a single solvent or elute through a gas chromatograph; therefore, a substantial portion typically remains unanalyzed. Most often the chemical analysis is performed on a fraction that extracts in organic solvents such as benzene, ether or hexane; consequently, information on the molecular composition of the water-soluble fraction is particularly sparse and incomplete. This paper investigates theoretically the characteristics of the water-soluble fraction by splicing together various strands of information from the literature. We identify specific compounds that are likely to contribute to the water-soluble fraction by juxtaposing observations regarding the extraction characteristics and the molecular composition of atmospheric particulate organics with compound-specific solubility and condensibility for a wide variety of organics. The results show that water-soluble organics, which constitute a substantial fraction of the total organic mass, include C2 to C7 multifunctional compounds (e.g., diacids, polyols, amino acids). The importance of diacids is already recognized; our results provide an impetus for new experiments to establish the atmospheric concentrations and sources of polyols, amino acids and other oxygenated multifunctional compounds.

TL;DR: A review of the current state of organic aerosol sampling, analysis, and simulation, examines the limitations of current technology, and presents prospects for the future is provided in this article, where the emphasis is on distilling findings from recent atmospheric, smog chamber, and theoretical studies to provide a coherent picture of what has been accomplished, especially during the last five years.

TL;DR: In this article, a framework is presented for combining the information content of different equivalent diameter measurements into a single coherent mathematical description of the particles, which allows the placing of constraints on particle density, dynamic shape factor (x), and fraction of internal void space.

Abstract: Different on-line submicron particle sizing techniques report different “equivalent diameters.” For example, differential mobility analyzers (DMAs) report electrical mobility diameter (dm ), while a number of recently developed instruments (such as the Aerodyne aerosol mass spectrometer, or AMS) measure vacuum aerodynamic diameter (dva ). Particle density and physical morphology (shape) have important effects on diameter measurements. Here a framework is presented for combining the information content of different equivalent diameter measurements into a single coherent mathematical description of the particles. We first present a review of the mathematical formulations used in the literature and their relationships. We then show that combining dm and dva measurements for the same particle population allows the placing of constraints on particle density, dynamic shape factor (x), and fraction of internal void space. The amount of information that can be deduced from the combination of dm and dm measurement...