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Aerosol distribution is of great relevance for air quality especially for the cities like Stuttgart which is located in a basin. To understand the impact of boundary layer mixing processes on local air quality and to validate the large eddy simulation (LES) model PAML-4U, we collected a comprehensive set of data from remote sensing, in-situ methods including radiosondes for the urban background of downtown Stuttgart. Stagnant meteorological conditions caused accumulation of aerosols during winter. Case studies show that clouds during previous nights can weaken temperature inversion and accelerate boundary layer mixing after sunrise. This is important for ground-level aerosol dilution during morning rush hours. Furthermore, our observations validate results of the LES model PALM-4U in terms of boundary layer heights and aerosol mixing for 48 hours. The simulated aerosol concentrations follow the trend of our observations but are still underestimated by a factor of 4.5 ± 2.1. This underestimation is mainly due to uncertainties of emissions and boundary conditions of the model. This paper firstly evaluates the PALM-4U model performance in simulating aerosol temporal-spatial distribution, which can help to improve the LES model and to better understand sources and sinks for air pollution as well as the role of horizontal and vertical transport. [ABSTRACT FROM AUTHOR]

Aerosol distribution is of great relevance for air quality especially for the cities like Stuttgart which is located in a basin. To understand the impact of boundary layer mixing processes on local air quality and to validate the large eddy simulation (LES) model PAML-4U, we collected a comprehensive set of data from remote sensing, in-situ methods including radiosondes for the urban background of downtown Stuttgart. Stagnant meteorological conditions caused accumulation of aerosols during winter. Case studies show that clouds during previous nights can weaken temperature inversion and accelerate boundary layer mixing after sunrise. This is important for ground-level aerosol dilution during morning rush hours. Furthermore, our observations validate results of the LES model PALM-4U in terms of boundary layer heights and aerosol mixing for 48 hours. The simulated aerosol concentrations follow the trend of our observations but are still underestimated by a factor of 4.5 ± 2.1. This underestimation is mainly due to uncertainties of emissions and boundary conditions of the model. This paper firstly evaluates the PALM-4U model performance in simulating aerosol temporal-spatial distribution, which can help to improve the LES model and to better understand sources and sinks for air pollution as well as the role of horizontal and vertical transport. [ABSTRACT FROM AUTHOR]

The apparent volatility of atmospheric organic aerosol (OA) particles is determined by their chemical composition and environmental conditions (e.g., ambient temperature). A quantitative, experimental assessment of volatility and the respective importance of these two factors remains challenging, especially in ambient measurements. We present molecular composition and volatility of oxygenated OA (OOA) particles in different rural, urban, and remote environments across the globe (including Chacaltaya, Bolivia; Alabama, U.S.; Hyytiälä, Finland; Stuttgart and Karlsruhe, Germany; and Delhi, India) based on deployments of a filter inlet for gases and aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO-CIMS). We find on average larger carbon numbers (nC) and lower oxygen-to-carbon (O:C) ratios at the urban sites (nC: 9.8±0.7; O:C: 0.76±0.03; average ± 1 standard deviation), compared to the rural (nC: 8.8±0.6; O:C: 0.80±0.05) and remote mountain stations (nC: 8.1±0.8; O:C: 0.91±0.07), indicative of different emission sources and chemistry. Compounds containing only carbon, hydrogen, and oxygen atoms (CHO) contribute highest to the total OOA mass at the rural sites (79.9±5.2 %), in accordance with their proximity to forested areas (66.2±5.5 % at the mountain sites and 72.6±4.3 % at the urban sites). The largest contribution of nitrogen-containing compounds (CHON) are found at the urban stations (27.1±4.3 %), consistent with their higher NOx levels. Besides, we parametrize OOA volatility (saturation mass concentrations, C sat) using molecular composition information and compare it with the bulk apparent volatility derived from thermal desorption of the OOA particles within the FIGAERO. We find differences in C sat values of up to ~3 orders of magnitude, and variation in thermal desorption profiles (thermograms) across different locations and systems. From our study, we draw the general conclusion that environmental conditions (e.g., ambient temperature) do not directly affect OOA apparent volatility, but rather indirectly by influencing the sources and chemistry of the environment and thus the chemical composition. The comprehensive global dataset provides results that show the complex thermodynamics and chemistry of OOA and their changes during its lifetime in the atmosphere, and that generally the chemical description of OOA suffices to predict its apparent volatility, at least qualitatively. Our study thus provides new insights that will help guide choices of e.g. descriptions of OOA volatility in different model frameworks which has been previously simplified due to challenges to measure and represent it in models. [ABSTRACT FROM AUTHOR]

The apparent volatility of atmospheric organic aerosol (OA) particles is determined by their chemical composition and environmental conditions (e.g., ambient temperature). A quantitative, experimental assessment of volatility and the respective importance of these two factors remains challenging, especially in ambient measurements. We present molecular composition and volatility of oxygenated OA (OOA) particles in different rural, urban, and remote environments across the globe (including Chacaltaya, Bolivia; Alabama, U.S.; Hyytiälä, Finland; Stuttgart and Karlsruhe, Germany; and Delhi, India) based on deployments of a filter inlet for gases and aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO CIMS). We find on average larger carbon numbers (nC) and lower oxygen-to-carbon (O:C) ratios at the urban sites (nC: 9.8±0.7; O:C: 0.76±0.03; average ± 1 standard deviation), compared to the rural (nC: 8.8±0.6; O:C: 0.80±0.05) and remote mountain stations (nC: 8.1±0.8; O:C: 0.91±0.07), indicative of different emission sources and chemistry. Compounds containing only carbon, hydrogen, and oxygen atoms (CHO) contribute highest to the total OOA mass at the rural sites (79.9±5.2%), in accordance with their proximity to forested areas (66.2±5.5% at the mountain sites and 72.6±4.3% at the urban sites). The largest contribution of nitrogen-containing compounds (CHON) are found at the urban stations (27.1±4.3%), consistent with their higher NOx levels. Besides, we parametrize OOA volatility (saturation mass concentrations, Csat) using molecular composition information and compare it with the bulk apparent volatility derived from thermal desorption of the OOA particles within the FIGAERO. We find differences in Csat values of up to ~3 orders of magnitude, and variation in thermal desorption profiles (thermograms) across different locations and systems. From our study, we draw the general conclusion that environmental conditions (e.g., ambient temperature) do not directly affect OOA apparent volatility, but rather indirectly by influencing the sources and chemistry of the environment and thus the chemical composition. The comprehensive global dataset provides results that show the complex thermodynamics and chemistry of OOA and their changes during its lifetime in the atmosphere, and that generally the chemical description of OOA suffices to predict its apparent volatility, at least qualitatively. Our study thus provides new insights that will help guide choices of e.g. descriptions of OOA volatility in different model frameworks which has been previously simplified due to challenges to measure and represent it in models. [ABSTRACT FROM AUTHOR]

We conducted a six-week measurement campaign in summer 2016 at a rural site about 11 km north of the city of Karlsruhe in southwest Germany in order to study the chemical composition and origin of aerosols in the upper Rhine valley. In particular, we deployed a single particle mass spectrometer (LAAPTOF) and an aerosol mass spectrometer (AMS) to provide complementary chemical information of the aerosol particles smaller than 2.5 µm. For the entire measurement period, the total aerosol particle mass was dominated by sodium salts contributing on average (36 ± 27) % to the total single particles. The total particulate organic compounds, sulfate, nitrate, and ammonium contributed on average (58 ± 12) %, (22 ± 7) %, (10 ± 1) %, and (9 ± 3) % to the total non-refractory particle mass, respectively. The regional transport model COSMO-ART was applied for source apportionment and to achieve a better understanding of the impact of complex transport pattern on the field observations. Combining field observations and model simulations, we attributed high particle numbers and SO2 concentrations observed at this rural site to industrial emissions from power plants and a refinery in Karlsruhe. In addition, two characteristic episodes with aerosol particle mass dominated by sodium salts particles compromising (70 ± 24) % of the total single particles and organic compounds comprising accounting for (77 ± 6) % of total non-refractory species, respectively, were investigated in detail. For the first episode, we identified relatively fresh and aged sea salt particles originating from the Atlantic Ocean more than 800 km away. These particles showed markers like m/z 129 C5H7NO2+ indicating the influence of anthropogenic emissions modifying their composition e.g., from chloride to nitrate salts during the long-range transport. For a 3-day episode including high organic mass concentrations, model simulations show that on average (74 ± 7) % of the particulate organics at this site were of biogenic origin. Detailed model analysis allowed us to find out that three subsequent peaks of high organic mass concentrations originated from different sources, including local emissions from the city and industrial area of Karlsruhe, regional transport from the city of Stuttgart (~64 km away), and potential local night-time formation and growths. Biogenic (forest) and anthropogenic (urban) emissions were mixed during transport and contributed to the formation of organic particles. In addition, topography, temperature inversion, and stagnant meteorological conditions also played a role in the build-up of higher organic particle mass concentrations. Furthermore, the model was evaluated using the field observations and corresponding sensitivity tests. The model results show good agreement with trends and concentrations observed for several trace gases (e.g., O3, NO2, and SO2) and aerosol particle compounds (e.g., ammonium and nitrate). However, the model underestimates the number of particles by an order of magnitude and underestimates the mass of organic particles by a factor of 2.3. The discrepancy was expected for particle number since the model does not include all nucleation processes. The missing organic mass indicates either an underestimated regional background, missing sources, and/or mechanisms in the model like night-time chemistry. This study demonstrates the potential of combining comprehensive field observations with dedicated transport modelling to understand the chemical composition and complex origin of aerosols. [ABSTRACT FROM AUTHOR]

Chemical composition and volatility of organic aerosol (OA) particles were investigated during July-August 2017 and February-March 2018 in the city of Stuttgart, one of the most polluted cities in Germany. Total non-refractory particle mass was measured with a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS; hereafter AMS). Aerosol particles were collected on filters and analyzed in the laboratory with a filter inlet for gases and aerosols coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (FIGAERO-HR-ToF-CIMS; hereafter CIMS), yielding the molecular composition of oxygenated OA (OOA) compounds. While the average organic mass loadings are lower in the summer period (5.1±3.2μgm-3) than in the winter period (8.4±5.6μgm-3), we find relatively larger mass contributions of organics measured by AMS in summer (68.8±13.4%) compared to winter (34.8±9.5%). CIMS mass spectra show OOA compounds in summer have O:C ratios of 0.82±0.02 and are more influenced by biogenic emissions, while OOA compounds in winter have O:C ratios of 0.89±0.06 and are more influenced by biomass burning emissions. Volatility parametrization analysis shows that OOA in winter is less volatile with higher contributions of low volatile organic compounds (LVOC) and extremely low volatile organic compounds (ELVOC). We partially explain this by the higher contributions of compounds with shorter carbon chain lengths and higher number of oxygen atoms, i.e. higher O:C ratios in winter. Organic compounds desorbing from the particles deposited on the filter samples also exhibit a shift of signal to higher desorption temperatures (i.e. lower apparent volatility) in winter. This is consistent with the relatively higher O:C ratios in winter, but may also be related to higher particle viscosity due to the higher contributions of larger molecular-weight LVOC and ELVOC, interactions between different species and/or particles (particle matrix), and/or thermal decomposition of larger molecules. The results suggest that whereas lower temperature in winter may lead to increased partitioning of semi-volatile organic compounds (SVOC) into the particle phase, this does not result in a higher overall volatility of OOA in winter, and that the difference in sources and/or chemistry between the seasons plays a more important role. Our study provides insights into the seasonal variation of molecular composition and volatility of ambient OA particles, and into their potential sources. [ABSTRACT FROM AUTHOR]

Single particle mass spectrometry (SPMS) is a useful, albeit not fully quantitative tool to determine chemical composition and mixing state of aerosol particles in the atmosphere. During a six-week field campaign in summer 2016 at a rural site in the upper Rhine valley near Karlsruhe city in southwest Germany, ~3.7 x 105 single particles were analyzed by a laser ablation aerosol particle time-of-flight mass spectrometer (LAAPTOF). Combining fuzzy classification, marker peaks, typical peak ratios, and laboratory-based reference spectra, seven major particle classes were identified. With the precise identification and well characterized overall detection efficiency (ODE) for this instrument, particle similarity can be transferred into corrected number fractions and further transferred into mass fractions. Considering the entire measurement period, Potassium rich and aromatics coated dust (class 5) dominated the particle number (46.5 % number fraction) and mass (36.0 % mass fraction); Sodium salts like particles (class 3) were the second lowest in number (3.5 %), but the second dominating class in terms of particle mass (25.3 %). This difference demonstrates the crucial role of particle mass quantification for SPMS data. Using corrections for maximum, mean, and minimum ODE, the total mass of the quantified particles measured by LAAPTOF accounts for ~12 %, ~25 %, and ~104 % of the total mass measured by an aerosol mass spectrometer (AMS) with a collection efficiency of 0.5. These two mass spectrometers show a good correlation (correlation coefficient γ > 0.6) regarding total mass for more than 70 % of the measurement time, indicating non-refractory species measured by AMS might originate from particles consisting of internally mixed non-refractory and refractory components. In addition, specific relationships of LAAPTOF ion intensities and AMS mass concentrations for non-refractory compounds were found for specific measurement periods. Furthermore, our approach allows for the first time to assign the non-refractory compounds measured by AMS to different particle classes. Overall AMS-nitrate was mainly arising from class 3, while class 5 was dominant during events rich in organic aerosol particles. [ABSTRACT FROM AUTHOR]

The laser ablation aerosol particles time-of-flight mass spectrometer (LAAPTOF, Aeromegt GmbH) is able to identify the chemical composition and mixing state of individual aerosol particles, and thus is a tool for elucidating their impacts on human health, visibility, ecosystem and climate. The overall detection efficiency (ODE) of the instrument we use was determined to range from ~(0.01 ± 0.01)% to ~(6.57 ± 2.38)% for polystyrene latex (PSL), ammonium nitrate (NH4NO3), and sodium chloride (NaCl) particles in the size rage of 200 to 2000nm. Reference mass spectra of 32 different particle types relevant for atmospheric aerosol (e.g. pure compounds NH4NO4, K2SO4, NaCl, oxalic acid, pinic acid, and pinonic acid; internal mixtures of e.g. salts, secondary organic aerosol, and metallic core-organic shell particles; more complex particles such as soot and dust particles) were determined. Our results show that internally mixed aerosol particles can result in spectra with new clusters of ions, rather than simply a combination of the spectra from the single components. An exemplary one-day ambient data set was analysed by classical Fuzzy-clustering leading to six different particle classes. Correlating these particle classes with the reference spectra as well as direct comparison of the ambient data with the reference spectra has proven how useful they are for the interpretation of field measurements, for e.g. grouping data, and identifying special particle types and potential sources. [ABSTRACT FROM AUTHOR]

Size, composition, and mixing state of individual aerosol particles can be analysed in real time using single particle mass spectrometry (SPMS). In SPMS, laser ablation is the most widely used method for desorption and ionization of particle components, often realizing both in one single step. Excimer lasers are well suited for this task due to their relatively high power density (107 W cm-2-1010 W cm-2) in nanosecond (ns) pulses at ultraviolet (UV) wavelengths, and short triggering times. However, varying particle optical properties and matrix effects make a quantitative interpretation of this analytical approach challenging. In atmospheric SPMS applications, this influences both the mass fraction of an individual particle that gets ablated, as well as the resulting mass spectral fragmentation pattern of the ablated material. The goal of the present study is to explore the use of shorter (femtosecond, fs) laser pulses for atmospheric SPMS, and to systematically investigate the influence of power density and pulse duration on airborne particle (polystyrene latex, SiO2, NH4NO3, NaCl, and custom-made core-shell particles) ablation and reproducibility of mass spectral signatures. We used a laser ablation aerosol time-of-flight single particle mass spectrometer (LAAPTOF, AeroMegt GmbH), originally equipped with an excimer laser (wavelength 193 nm, pulse width 8 ns, pulse energy 4 mJ), and coupled it to an fs-laser (Spectra Physics Solstice-100F ultrafast laser) with similar pulse energy, but longer wavelengths (266 nm with 100 fs and 0.2 mJ, 800 nm with 100 fs and 4 mJ, respectively). Generally, mass spectra exhibit an increase in ion intensities (factor 1 to 5) with increasing laser power density (~ 108 W cm-2 to ~ 1013 W cm-2) from ns- to fs-laser. At the same time, fs-laser ablation produces spectra with larger ion fragments and ion clusters, as well as clusters with oxygen, which does not render spectra interpretation more simple compared to ns-laser ablation. Quantification of ablated material remains difficult due to incomplete ionization of the particle. Furthermore, the fs-laser application still suffers from limitations in triggering it in a useful timeframe. Further tests are needed to test potential advantages of fs- over ns-laser ablation in atmospheric SPMS. [ABSTRACT FROM AUTHOR]