Abstract. Global measurements of organic aerosol (OA) concentrations and chemical composition remain limited and unevenly distributed. While monitoring networks, including the globally distributed Surface Particulate Matter Network (SPARTAN), provide an established framework for measurements, their current methodologies do not fully support comprehensive OA characterization. Aerosol Mass Spectrometry (AMS) is widely used for real-time OA composition measurements, but its cost, complexity, and logistical requirements limit long-term, multi-site online deployment, particularly at the global scale. Here we develop and evaluate an offline AMS methodology to characterize OA in particulate matter collected on Teflon filters routinely used by monitoring networks. Using a commercial ultrasonic nebulizer coupled with a syringe pump, this offline method is highly reproducible, requires small extract volumes (2 mL), offers low detection limits (1.7 µg OA and 0.43 µg sulfate per filter), and achieves higher nebulization efficiency than previous methods. We evaluate this offline AMS method by co-located online AMS observations. We find that oxygenated OA is effectively recovered (64 ± 28 %) while the recovery is lower for hydrocarbon-like OA due to its limited water solubility. This approach offers new capability for SPARTAN and is readily adaptable to other monitoring networks. Its application across networks will broaden the spatiotemporal coverage of AMS-based OA measurements and improve methodological and instrumental consistency to support ongoing efforts to build a long-term, globally consistent OA dataset.

Long-range transport (LRT) from the Asian continent significantly influences PM2.5 chemical composition on the Korean Peninsula, yet its species-specific effects remain poorly constrained across different urban environments. This study used multi-year SPARTAN filter-based measurements, complemented by AirKorea and NIER AQRC observations, to quantify LRT effects on PM2.5 chemical composition in Seoul (2019-2023; 50 samples) and Ulsan (2021-2024; 53 samples), South Ko Long-range transport (LRT) from the Asian continent significantly influences PM2.5 chemical composition on the Korean Peninsula, yet its species-specific effects remain poorly constrained across different urban environments. This study used multi-year SPARTAN filter-based measurements, complemented by AirKorea and NIER AQRC observations, to quantify LRT effects on PM2.5 chemical composition in Seoul (2019-2023; 50 samples) and Ulsan (2021-2024; 53 samples), South Korea. 9-Day samples were classified using the fraction of back-trajectories passing through the Yellow Sea (YS), and the top and bottom 20% cases were compared. Under YS Highest conditions, PM2.5 mass increased by 15.4% in Seoul and 25.6% in Ulsan. In Seoul, sulfate nearly doubled from 2.39 to 4.56 mu g/m(3), ammonium increased from 1.17 to 1.85 mu g/m(3) (+58%), sea salt from 0.20 to 0.31 mu g/m(3), and fine soil from 2.14 to 3.14 mu g/m(3), consistent with enhanced continental outflow across the YS for most inorganic components. SPARTAN nitrate showed no clear increase despite elevated NIER nitrate (similar to 2.7 to similar to 4.7 mu g/m(3)), likely reflecting volatilization losses inherent to long-term filter sampling, while OC decreased from 3.93 to 3.01 mu g/m(3), indicating a stronger seasonal than transport-driven control on carbonaceous components. In Ulsan, nitrate increased sharply from 0.29 to 2.04 mu g/m(3), whereas sulfate decreased from 3.53 to 3.22 mu g/m(3) and sea salt/fine soil showed limited enhancement, suggesting mixed influences from transport, local industry, coastal meteorology, and seasonality. These contrasting chemical signatures between the two cities, further supported by precursor gas comparisons, demonstrate that a common YS-based LRT classification can produce markedly different PM2.5 responses depending on regional geography and meteorology, highlighting the need for species-resolved, site-specific LRT assessment.

Characterizing black carbon (BC) on a fine scale globally is essential for understanding its climate and health impacts. However, sparse BC mass measurements in different parts of the world and coarse model resolution have inhibited evaluation of global BC emission inventories. Here, we apply globally distributed BC mass measurements from the Surface Particulate Matter Network (SPARTAN) and complementary measurement networks to evaluate contemporary BC emission inventories. We use a global chemical transport model (GEOS-Chem) in its high-performance configuration (GCHP) for high-resolution simulations to relate BC emissions to ambient concentrations for comparison with measurements. Here we find that simulations using the Community Emissions Data System (CEDS) emission inventory exhibit skill (r2 = 0.73) in representing variability in SPARTAN measurements across primarily developed regions with low BC concentrations but exhibit pronounced discrepancy (r2 = 0.00019) across high-BC regions in the Global South, underestimating BC by 38%. Alternative inventories (EDGAR, HTAP) yield similar results. These findings motivate renewed attention to the challenging task of characterizing BC emissions from low- and middle-income countries.

Accurate representation of mineral dust remains a challenge for global air quality or climate models due to inadequate parametrization of the emission scheme, removal mechanisms, and size distribution. While various studies have constrained aspects of dust emission fluxes and/or dust optical depth, annual mean surface dust concentrations still vary by factors of 5-10 among models. In this study, we focus on improving the annual simulation of fine dust in the GEOS-Chem chemical transport model, leveraging recent mechanistic understanding of dust source and removal, and reconciling the size differences between models and ground-based measurements. Specifically, we conduct sensitivity simulations using GEOS-Chem in its high performance configuration (GCHP) version 14.4.1 to investigate the effects of mechanism or parameter updates on annual mean concentrations. The results are evaluated by comparisons versus Deep Blue satellite-based aerosol optical depth (AOD) and AErosol RObotic NETwork (AERONET) ground-based AOD for total column abundance, and versus the Surface Particulate Matter Network (SPARTAN) for novel measurements of surface PM2.5 dust concentrations. Reconciling modelled geometric diameter versus measured aerodynamic diameter is important for consistent comparison. The two-fold overestimation of surface fine dust in the standard model is alleviated by 39 % without degradation of total column abundance by implementing a new physics-based dust emission scheme with better spatial distribution. Further reduction by 20 % of the overestimation of surface PM2.5 dust is achieved through reducing the mass fraction of emitted fine dust based on the brittle fragmentation theory, and explicit tracking of three additional fine mineral dust size bins with updated parametrization for below-cloud scavenging. Overall, these developments reduce the normalized mean difference against surface fine dust measurements from SPARTAN from 94 % to 35 %, while retaining comparable skill of total column abundance against satellite and ground-based AOD.

Reliable elemental analysis is important for understanding mineral dust mass concentrations, composition, sources, and atmospheric processing. X-ray attenuation of light elements in widely used X-ray fluorescence (XRF) measurements can lead to underestimated dust mass and inaccurate dust composition, yet attenuation corrections are often neglected in ambient particulate matter (PM) analysis. This study experimentally quantifies attenuation for silicon and aluminum by comparing XRF and gravimetric measurements of samples with known compositions. Silica (SiO2), alumina (Al2O3), and Arizona test dust (ATD) were aerosolized and collected on Teflon filters to generate samples with varying mass loadings and particle size ranges. Results validated that attenuation increases with both mass loading and particle size. Greater Si attenuation observed in ATD than in SiO2 at equivalent mass loading and size range indicates that other crustal elements enhance Si attenuation. Theoretical models considering only mass loading or particle size underestimated the measured attenuation. We developed empirical equations to correct for Si and Al attenuation. Applying these equations, with a size scaling factor for nondust species, to ambient dust-dominated PM samples from the global Surface PARTiculate mAtter Network (SPARTAN) increased dust concentrations by 21% in PM2.5 and 29% in PM10. This work demonstrates the importance of considering attenuation effects in XRF analysis for accurate dust inference from measured elements.

Using the Surface Particulate Matter Network (SPARTAN) and Aerosol Robotic Network (AERONET), we investigated the relationship between aerosol chemical composition and optical properties across 14 global sites. The mass concentrations of ammonium sulfate (AS), ammonium nitrate (AN), fine soil (FS), and black carbon (BC) from SPARTAN were collocated with aerosol optical properties (aerosol optical depth (AOD), fine mode fraction (FMF), and single scattering albedo (SSA)) from AERONET. Significant differences in the optical properties of samples from 2016 to 2023 were identified based on the mass and mass ratios of the chemical components. For the BC-FS relationship in the data set used in this study, increased FS mass lowered FMF and dSSABC-FS (SSA440-SSA870) by approximately 0.033 and 0.005 per 1 μg/m3, respectively. Higher ratios of nonabsorbing components (AS and AN) to BC (w = (AS + AN)/(AS + AN + BC)) increased SSA at all wavelengths. The correlation between w and SSA was stronger at longer wavelengths, with SSA440 and SSA1020 increasing by approximately 0.026 and 0.046 per 10% increase in w from the data set, respectivley. Site-specific results showed that dSSAw and rSSA (SSA440/SSA1020) increased as the BC proportion rose (w decreased). This study emphasizes the utility of both dSSA and rSSA, alongside single-wavelength SSA, in understanding aerosol behavior. Integrating columnar optical data with surface-level chemical measurements, the combined SPARTAN and AERONET approach offers valuable insight into aerosol classification, behavior, and atmospheric impacts.

Ambient fine particulate matter (PM2.5) is the leading global environmental determinant of mortality. However, large gaps exist in ground-based PM2.5 monitoring. Satellite remote sensing of aerosol optical depth (AOD) offers information to help fill these gaps worldwide when augmented with a modeled PM2.5–AOD relationship. This study aims to understand the spatial pattern and driving factors of this relationship by examining η (PM2.5AOD) using both observations and modeling. A global observational estimate of η for the year 2019 is inferred from 6870 ground-based PM2.5 measurement sites and satellite-retrieved AOD. The global chemical transport model GEOS-Chem, in its high-performance configuration (GCHP), is used to interpret the observed spatial pattern of annual mean η. Measurements and the GCHP simulation consistently identify a global population-weighted mean η value of 96–98 µg m−3, with regional values ranging from 59.8 µg m−3 in North America to more than 190 µg m−3 in Africa. The highest η value is found in arid regions, where aerosols are less hygroscopic due to mineral dust, followed by regions strongly influenced by surface aerosol sources. Relatively low η values are found over regions distant from strong aerosol sources. The spatial correlation of observed η values with meteorological fields, aerosol vertical profiles, and aerosol chemical composition reveals that spatial variation in η is strongly influenced by aerosol composition and aerosol vertical profiles. Sensitivity tests with globally uniform parameters quantify the effects of aerosol composition and aerosol vertical profiles on spatial variability in η, exhibiting a population-weighted mean difference in aerosol composition of 12.3 µg m−3, which reflects the determinant effects of composition on aerosol hygroscopicity and aerosol optical properties, and a population-weighted mean difference in the aerosol vertical profile of 8.4 µg m−3, which reflects spatial variation in the column–surface relationship.

Monitoring particulate matter (PM) air pollution in terms of both concentration and composition, is very important due to its effects on human health and climate. In the PRIMARY project we aim at retrieving the aerosol composition from space using the hyperspectral observations from the Italian Space Agency's PRISMA mission. To this end, we are developing a machine learning algorithm trained with synthetic top-of-atmosphere reflectances and underlying aerosol fields. As part of this process, we plan to use the global forecasts from the Copernicus Atmosphere Monitoring Service (CAMS) as the core to generate this synthetic dataset. However, to proceed in this direction, a preliminary assessment of the reliability of this model-based dataset when compared to observations is necessary, also to bias correct the output if needed. With this aim, we assess the representation of the aerosol chemical composition and the related optical properties at selected globally distributed sites in CAMS, comparing the simulations with near-surface aerosol chemical analyses from the SPARTAN network and column sun-photometer observations from the AERONET network. We found that CAMS forecasts skills changed over time due to updates in the modelling system, with the latter two version cycles (46 and 47) being similar. Generally, they reproduce the aerosol composition within a factor of 2. We found a substantial overestimation of organic matter (OM) by a factor of 3. Applying a correcting factor to OM (constant at the global level) warrants a much more realistic representation of PM2.5 total mass and relative fraction of single species in CAMS. From the so derived CAMS aerosol-speciated profiles, we calculate aerosol optical properties, needed for subsequent use in a radiative transfer model. Comparison against AERONET indeed shows that OM bias correction resulted in improvements in Extinction Ångstrom Exponent (α440nm870nm). Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Asymmetry Parameter (g) simulations resulted slightly degraded, confirming the possibility of using CAMS as the base for a synthetic retrieval training dataset.

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 μg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 μg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.

The Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) measures the hygroscopicity of atmospheric particles, and many atmospheric processes that change this hygroscopicity also change the atmospheric size distribution. Two assumptions made during H-TDMA inversion create spurious hygroscopic trends as a function of the changing inlet size distribution. These two assumptions—that the particles exiting the first Differential Mobility Analyzer (DMA1) are singly charged and that the inlet size distribution has a slope of zero (flat)— generate Multi-Charge Dispersion (MCD) bias and Slope bias, respectively. First, we use a model, named TAO, to show that the inlet size distribution could theoretically change the measured ammonium sulfate hygroscopicity by 10%–20% as a function of diameter or experimental time with no change in relative humidity. Secondly, we show experimentally that aerosol emitted from the flaming combustion of grass creates MCD bias. In this experiment, we measure the CPC response of the first three charges and invert these responses using a new routine named Junior. Junior's inversion of each charge shows that one growth factor distribution describes all measured diameters (no growth dependence on diameter). As in the modeling study above, previous publications of this aerosol system, using traditional inversion assumptions, report a decrease in hygroscopicity as DMA1 diameter increases. Unlike traditional inversions, Junior's inversion does not assume the particles are singly charged nor does it make the flat inlet size distribution assumption. Instead, both the inlet size distribution and each charge's CPC response are measured quantities. Thus, the discrepancy between our inversion results and previous publications is likely due to the traditional inversion routine assumptions. This underscores the importance for accounting for Slope and MCD bias during inversions. Experimental results should be carefully analyzed when reporting hygroscopic trends with respect to diameter or experimental time when using the traditional inversion assumptions.

Novel designs and materials for filtering face-piece respirators (FFRs) have been disseminated in response to shortages during the COVID-19 pandemic. Since filtration efficiency depends on particle diameter and air face velocity, the relevance of material filtration or prototype fit data depends on test conditions. We investigate whether characterizing a material in a filter holder at a range of face velocities enabled precise prediction of the filtration performance of a novel sewn mask design. While larger particles (> 500 nm) are more relevant for inhalation exposure to respiratory emissions, we compare this mask and a N95 FFR (as a control) with smaller particles more similar to those in the N95 test method. Sewn from sterilization wrap, our mask (sealed to a mannequin head with silicone) filters 85 ± 1

Significant evaporation of pure aerosols in a Volatility Tandem Differential Mobility Analyzer (V-TDMA) creates two Condensation Particle Counter (CPC) response peaks. Two hypotheses for the observed peaks have been proposed: the existence of two phases or the separation of the singly charged experimental size distribution from the remaining experimental size distributions with charges greater than 1 (charge separation). To explore this observation, we atomized pure levoglucosan aerosol and evaporated the aerosol until two peaks formed. We used an additional classifier and neutralizer to select particles from each of the two peaks and assessed the number of charges on the particles. The smaller diameter peak contained singly charged particles, and the larger diameter peak contained the remaining charges. The charge separation hypothesis alone accounts for the two-peak observations. We used a new V-TDMA model named TAO and show that charge separation should occur in other pure components as well. The TAO model was then used to display the impact of different DMA transfer functions, different inlet size distributions, and different oven residence time distributions (RTDs) on the CPC response. Large errors are possible when direct measurement of the RTD is not performed or when wide RTDs are used. We recommend use of narrow transfer functions with narrow RTDs to detect charge separation. When the singly charged CPC response is isolated (smaller diameter peak in the two peak response), accurate estimations of vapor pressure can be recovered, assuming accurate values for gas phase diffusivity, surface energy, particle density, etc. are used. Copyright (c) 2020 American Association for Aerosol Research

This document intends to provide information about sea salt aerosol sourced from the southern hemisphere.Justification for the study is given as a lack of southern hemisphere measurements and underestimation of low-level cloud cover.The measurements come from a 23-day ship voyage off the coast of New Zealand.Several chemical speciation measurements were taken along with VH-TDMA (water) and UFO-TDMA (ethanol) measurements.The author uses statistical analysis of the many variables to survey for correlations.Some of those correlations do not have legitimate causation.The document ends by trying to resolve the issues using OCEANFILMS (vs ZSR).The amount of work is significant and clearly represents measurements from the southern hemisphere.Some changes should be made prior to full publication.

We create and qualify a Volatility and Hygroscopicity Tandem Differential Mobility Analyzer (VH-TDMA) for the study of aerosols. This VH-TDMA measures size distributions, volatility, and hygroscopicity and includes an auxiliary conditioner that allows quick connection to other external aerosol conditioners. The differential mobility analyzers are not temperature controlled, allowing the surrounding environment to influence the measurement conditions, and this is fully accounted for when measuring aerosol volatility and hygroscopicity. For the volatility conditioner, the VH-TDMA uses a 15 m coil of tubing in an oven to evaporate aerosol samples at elevated temperatures. We measured several single component model aerosols to qualify the differential mobility particle sizer (DMPS) channel and each of the conditioners: hygroscopicity and volatility. Due to insufficient power supply calibration in this study, the TDMA channel is limited to particle sizes greater than 70 nm. The DMPS channel was able to reproduce ammonium sulfate size distributions when compared to common scanning mobility particle sizers. For hygroscopicity, the standard deviation in the measured ammonium sulfate growth factors was 0.03 over a 4-h experiment. From this data, the TDMA has an observed relative humidity error of +/- 0.6% with manufacturer reported error of +/- 1.2% relative humidity. The volatility channel reproduced the previously published saw tooth pattern of room temperature saturation vapor pressures from atomized C3-C9 diacids. The maximum percent difference in room temperature saturation vapor pressure was approximately 80%. The enthalpy of sublimation derived from the diacids increased monotonically (except for suberic acid) and resembled measurements from mass effusion techniques.

The presence of atmospheric brown carbon (BrC) has been the focus of many recent studies. These particles, predominantly emitted from smoldering biomass burning, absorb light in the near-ultraviolet and short visible wavelengths and offset the radiative cooling effects associated with organic aerosols. Particle density dictates their transport properties and is an important parameter in climate models and aerosol instrumentation algorithms, but our knowledge of this particle property is limited, especially as functions of combustion temperature and fuel type. We measured the effective density (ρeff) and optical properties of primary BrC aerosol emitted from smoldering combustion of Boreal peatlands. Energy transfer into the fuel was controlled by selectively altering the combustion ignition temperature, and we find that the particle ρeff ranged from 0.85 to 1.19 g cm-3 corresponding to ignition temperatures from 180 to 360 °C. BrC particles exhibited spherical morphology and a constant 3.0 mass-mobility exponent, indicating no internal microstructure or void spaces. Upon partial thermal volatilization, ρeff of the remaining particle mass was confined to a narrow range between 0.9 and 1.1 g cm-3. These findings lead us to conclude that primary BrC aerosols from biomass burning have homogeneous internal composition, and their ρeff is in fact their actual density.

Facilitated transport metal affinity membranes that incorporate metal affinity ligands are being investigated as a recovery scheme for specific amino acids (i.e. histidine) and proteins. The inclusion of metal affinity ligands as fixed site carriers within poly(vinyl alcohol) gel membranes resulted in increases in the mass transfer coefficient of histidine and increases in the selectivity of histidine to a noninteracting amino acid control, phenylalanine. Membranes containing chelated Cu+2 or Co+2 exhibited the largest increase in histidine mass transfer rate and those containing Ni+2 or Zn+2 displayed no increase in mass transfer coefficient relative to the control membrane. The effect of chelated metal type on histidine transport was similar to trends exhibited by other metal affinity separation methods.