53 research outputs found

    Organic coating on sulfate and soot particles during late Summer in the Svalbard Archipelago

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    14 pages, 8 figures, 1 table, supplement https://doi.org/10.5194/acp-19-10433-2019Interaction of anthropogenic particles with radiation and clouds plays an important role in Arctic climate change. The mixing state of aerosols is a key parameter to influence aerosol radiation and aerosol–cloud interactions. However, little is known of this parameter in the Arctic, preventing an accurate representation of this information in global models. Here we used transmission electron microscopy with energy-dispersive X-ray spectrometry, scanning electron microscopy, nanoscale secondary ion mass spectrometry, and atomic forces microscopy to determine the size and mixing state of individual sulfate and carbonaceous particles at 100 nm to 2 µm collected in the Svalbard Archipelago in summer. We found that 74 % by number of non-sea-salt sulfate particles were coated with organic matter (OM); 20 % of sulfate particles also had soot inclusions which only appeared in the OM coating. The OM coating is estimated to contribute 63 % of the particle volume on average. To understand how OM coating influences optical properties of sulfate particles, a Mie core–shell model was applied to calculate optical properties of individual sulfate particles. Our result shows that the absorption cross section of individual OM-coated particles significantly increased when assuming the OM coating as light-absorbing brown carbon. Microscopic observations here suggest that OM modulates the mixing structure of fine Arctic sulfate particles, which may determine their hygroscopicity and optical propertiesThis work was funded by the National Natural Science Foundation of China (41622504, 41575116, 31700475) and the Hundred Talents Program in Zhejiang University. Zongbo Shi acknowledges funding from NERC (NE/S00579X/1)Peer Reviewe

    Strong anthropogenic control of secondary organic aerosol formation from isoprene in Beijing

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    Isoprene-derived secondary organic aerosol (iSOA) is a significant contributor to organic carbon (OC) in some forested regions, such as tropical rainforests and the Southeastern US. However, its contribution to organic aerosol in urban areas that have high levels of anthropogenic pollutants is poorly understood. In this study, we examined the formation of anthropogenically influenced iSOA during summer in Beijing, China. Local isoprene emissions and high levels of anthropogenic pollutants, in particular NOx and particulate SO2-4 , led to the formation of iSOA under both high- A nd low-NO oxidation conditions, with significant heterogeneous transformations of isoprene-derived oxidation products to particulate organosulfates (OSs) and nitrooxyorganosulfates (NOSs). Ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry was combined with a rapid automated data processing technique to quantify 31 proposed iSOA tracers in offline PM2.5 filter extracts. The co-elution of the inorganic ions in the extracts caused matrix effects that impacted two authentic standards differently. The average concentration of iSOA OSs and NOSs was 82.5 ngm-3, which was around 3 times higher than the observed concentrations of their oxygenated precursors (2-methyltetrols and 2-methylglyceric acid). OS formation was dependant on both photochemistry and the sulfate available for reactive uptake, as shown by a strong correlation with the product of ozone (O3) and particulate sulfate (SO2-4). A greater proportion of high-NO OS products were observed in Beijing compared with previous studies in less polluted environments. The iSOA-derived OSs and NOSs represented 0.62% of the oxidized organic aerosol measured by aerosol mass spectrometry on average, but this increased to ∼ 3% on certain days. These results indicate for the first time that iSOA formation in urban Beijing is strongly controlled by anthropogenic emissions and results in extensive conversion to OS products from heterogenous reactions

    Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China

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    Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µgm−3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species

    An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography : Implications for aerosol pH estimate

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    Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl-, SO2-4, NO-3, NHC4 and KC. However, F-, Mg2C and Ca2C were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO2-4, NO-3 and NHC4 generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl-from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl-, SO2-4, NO-3, NHC4 and KC across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl-, SO2-4, NO-3, NHC4 and KC decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE/CE) and ion balance (anions-cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent
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