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The formation of black carbon fractal aggregates (BCFAs) from combustion and subsequent ageing involves several stages resulting in modifications of particle size, morphology, and composition over time. To understand and quantify how each of these modifications influences the BC radiative forcing, the optical properties of BCFAs are modelled. Owing to the high computational time involved in numerical modelling, there are some gaps in terms of data coverage and knowledge regarding how optical properties of coated BCFAs vary over the range of different factors (size, shape, and composition). This investigation bridged those gaps by following a state-of-the-art description scheme of BCFAs based on morphology, composition, and wavelength. The BCFA optical properties were investigated as a function of the radius of the primary particle (ao), fractal dimension (Df), fraction of organics (forganics), wavelength (λ), and mobility diameter (Dmob). The optical properties are calculated using the multiple-sphere T-matrix (MSTM) method. For the first time, the modelled optical properties of BC are expressed in terms of mobility diameter (Dmob), making the results more relevant and relatable for ambient and laboratory BC studies. Amongst size, morphology, and composition, all the optical properties showed the highest variability with changing size. The cross sections varied from 0.0001 to 0.1 µm2 for BCFA Dmob ranging from 24 to 810 nm. It has been shown that MACBC and single-scattering albedo (SSA) are sensitive to morphology, especially for larger particles with Dmob > 100 nm. Therefore, while using the simplified core–shell representation of BC in global models, the influence of morphology on radiative forcing estimations might not be adequately considered. The Ångström absorption exponent (AAE) varied from 1.06 up to 3.6 and increased with the fraction of organics (forganics). Measurement results of AAE ≫ 1 are often misinterpreted as biomass burning aerosol, it was observed that the AAE of purely black carbon particles can be ≫ 1 in the case of larger BC particles. The values of the absorption enhancement factor (Eλ) via coating were found to be between 1.01 and 3.28 in the visible spectrum. The Eλ was derived from Mie calculations for coated volume equivalent spheres and from MSTM for coated BCFAs. Mie-calculated enhancement factors were found to be larger by a factor of 1.1 to 1.5 than their corresponding values calculated from the MSTM method. It is shown that radiative forcings are highly sensitive to modifications in morphology and composition. The black carbon radiative forcing ΔFTOA (W m−2) decreases up to 61 % as the BCFA becomes more compact, indicating that global model calculations should account for changes in morphology. A decrease of more than 50 % in ΔFTOA was observed as the organic content of the particle increased up to 90 %. The changes in the ageing factors (composition and morphology) in tandem result in an overall decrease in the ΔFTOA. A parameterization scheme for optical properties of BC fractal aggregates was developed, which is applicable for modelling, ambient, and laboratory-based BC studies. The parameterization scheme for the cross sections (extinction, absorption, and scattering), single-scattering albedo (SSA), and asymmetry parameter (g) of pure and coated BCFAs as a function of Dmob were derived from tabulated results of the MSTM method. Spanning an extensive parameter space, the developed parameterization scheme showed promisingly high accuracy up to 98 % for the cross sections, 97 % for single-scattering albedos (SSAs), and 82 % for the asymmetry parameter (g).

Background Data from extensive mobile measurements (MM) of air pollutants provide spatially resolved information on pedestrians’ exposure to particulate matter (black carbon (BC) and PM2.5 mass concentrations). Objective We present a distributional regression model in a Bayesian framework that estimates the effects of spatiotemporal factors on the pollutant concentrations influencing pedestrian exposure. Methods We modeled the mean and variance of the pollutant concentrations obtained from MM in two cities and extended commonly used lognormal models with a lognormal-normal convolution (logNNC) extension for BC to account for instrument measurement error. Results The logNNC extension significantly improved the BC model. From these model results, we found local sources and, hence, local mitigation efforts to improve air quality, have more impact on the ambient levels of BC mass concentrations than on the regulated PM2.5. Significance Firstly, this model (logNNC in bamlss package available in R) could be used for the statistical analysis of MM data from various study areas and pollutants with the potential for predicting pollutant concentrations in urban areas. Secondly, with respect to pedestrian exposure, it is crucial for BC mass concentration to be monitored and regulated in areas dominated by traffic-related air pollution.

Ice-nucleating particles (INPs) initiate the primary ice formation in clouds at temperatures above ca. −38 ∘C and have an impact on precipitation formation, cloud optical properties, and cloud persistence. Despite their roles in both weather and climate, INPs are not well characterized, especially in remote regions such as the Arctic. We present results from a ship-based campaign to the European Arctic during May to July 2017. We deployed a filter sampler and a continuous-flow diffusion chamber for offline and online INP analyses, respectively. We also investigated the ice nucleation properties of samples from different environmental compartments, i.e., the sea surface microlayer (SML), the bulk seawater (BSW), and fog water. Concentrations of INPs (NINP) in the air vary between 2 to 3 orders of magnitudes at any particular temperature and are, except for the temperatures above −10 ∘C and below −32 ∘C, lower than in midlatitudes. In these temperature ranges, INP concentrations are the same or even higher than in the midlatitudes. By heating of the filter samples to 95 ∘C for 1 h, we found a significant reduction in ice nucleation activity, i.e., indications that the INPs active at warmer temperatures are biogenic. At colder temperatures the INP population was likely dominated by mineral dust. The SML was found to be enriched in INPs compared to the BSW in almost all samples. The enrichment factor (EF) varied mostly between 1 and 10, but EFs as high as 94.97 were also observed. Filtration of the seawater samples with 0.2 µm syringe filters led to a significant reduction in ice activity, indicating the INPs are larger and/or are associated with particles larger than 0.2 µm. A closure study showed that aerosolization of SML and/or seawater alone cannot explain the observed airborne NINP unless significant enrichment of INP by a factor of 105 takes place during the transfer from the ocean surface to the atmosphere. In the fog water samples with −3.47 ∘C, we observed the highest freezing onset of any sample. A closure study connecting NINP in fog water and the ambient NINP derived from the filter samples shows good agreement of the concentrations in both compartments, which indicates that INPs in the air are likely all activated into fog droplets during fog events. In a case study, we considered a situation during which the ship was located in the marginal sea ice zone and NINP levels in air and the SML were highest in the temperature range above −10 ∘C. Chlorophyll a measurements by satellite remote sensing point towards the waters in the investigated region being biologically active. Similar slopes in the temperature spectra suggested a connection between the INP populations in the SML and the air. Air mass history had no influence on the observed airborne INP population. Therefore, we conclude that during the case study collected airborne INPs originated from a local biogenic probably marine source.

The interaction between water vapor and aerosol nanoparticles is of great significance in atmospheric processes. However, current knowledge of hygroscopicity of sub-10 nm organic nanoparticles and their concentration-dependent thermodynamic properties (e.g., water activity) in the highly supersaturated concentration range is scarcely available. In this study, we investigate the size dependence of hygroscopicity of organics (i.e., levoglucosan, D-glucose) in size down to 6 nm using a nano-hygroscopicity tandem differential mobility analyzer (nano-HTDMA). There is a weak size dependence of the hygroscopic growth factor observed for levoglucosan and D-glucose nanoparticles with diameters down to 20 nm. However, a clear size-dependent hygroscopic growth factor is observed for D-glucose nanoparticles down to 6 nm in size. A reduction in diameters of sub-20 nm levoglucosan is observed at the dry RHs, which is explained by partial levoglucosan evaporation into gas phase, indicting high impact of volatility of sub-20 nm levoglucosan aerosol nanoparticles. However, this also means that the hygroscopic growth factors of levoglucosan nanoparticles with diameters below 20 nm are not possible to be determined. The use of water activity parameterization models proposed by Kreidenweis et al. (2005) (KD, Köhler), the Extend-Aerosol Inorganic Model (E-AIM (standard UNIFAC), and Differential Köhler Analysis (DKA) method is to determine thermodynamic properties (e.g., water activity) of levoglucosan and D-glucose nanodroplets as a function of solute concentration, respectively. Predicated water activity for these aqueous organic solutions (i.e., levoglucosan, D-glucose) from the different methods are similar to observations from references in the low solute concentration (< 20 mol kg-1), while a quite difference is found in the high solute concentration (> 20 mol kg-1). In addition, we compare hygroscopicity measurements for levoglucosan and D-glucose nanoparticles with the E-AIM (standard UNIFAC), the ideal solution theory, and DKA predictions, respectively. The ideal solution theory describes well the measured hygroscopic growth factors of levoglucosan with diameters down to 20 nm and D-glucose nanoparticles with diameters higher than 60 nm, respectively, while the E-AIM (standard UNIFAC) model can successfully predict the growth factors of levoglucosan with diameters from 100 down to 6 nm at RH above 88–40 % (e.g., at RH above 88 % for 100 nm D-glucose, at RH above 40 % for 6 nm D-glucose). The use of the DKA method leads to a good agreement with measured hygroscopic growth factors of D-glucose aerosol nanoparticles with diameters from 100 down to 6 nm.

In the event of a failure of a nuclear power plant with release of radioactive material into the atmosphere, dispersion modelling is used to understand how the released radioactivity is spread. For the dispersion of particles, Lagrangian particle dispersion models (LPDMs) are commonly used, in which model particles, representing the released material, are transported through the atmosphere. These model particles are usually inert and undergo only first-order processes such as dry deposition and simplified wet deposition along the path through the atmosphere. Aerosol dynamic processes including coagulation, condensational growth, chemical interactions, formation of new particles and interaction with new aerosol sources are usually neglected in such models. The objective of this study is to analyse the impact of these advanced aerosol dynamic processes if they were to be included in LPDM simulations for use in radioactive preparedness. In this investigation, a fictitious failure of a nuclear power plant is studied for three geographically and atmospherically different sites. The incident was simulated with a Lagrangian single-trajectory box model with a new simulation for each hour throughout a year to capture seasonal variability of meteorology and variation in the ambient aerosol. (a) We conclude that modelling of wet deposition by incorporating an advanced cloud parameterization is advisable, since it significantly influence simulated levels of airborne and deposited activity including radioactive hotspots, and (b) we show that inclusion of detailed ambient-aerosol dynamics can play a large role in the model result in simulations that adopt a more detailed representation of aerosol–cloud interactions. The results highlight a potential necessity for implementation of more detailed representation of general aerosol dynamic processes into LPDMs in order to cover the full range of possible environmental characteristics that can apply during a release of radionuclides into the atmosphere.

The identification of different sources of the carbonaceous aerosol (organics and black carbon) was investigated at a mountain forest site located in central Germany from September to October 2010 to characterize incoming air masses during the Hill Cap Cloud Thuringia 2010 (HCCT-2010) experiment. The near-PM1 chemical composition, as measured by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), was dominated by organic aerosol (OA; 41 %) followed by sulfate (19 %) and nitrate (18 %). Source apportionment of the OA fraction was performed using the multilinear engine (ME-2) approach, resulting in the identification of the following five factors: hydrocarbon-like OA (HOA; 3 % of OA mass), biomass burning OA (BBOA; 13 %), semi-volatile-like OA (SV-OOA; 19 %), and two oxygenated OA (OOA) factors. The more oxidized OOA (MO-OOA, 28 %) was interpreted as being influenced by aged, polluted continental air masses, whereas the less oxidized OOA (LO-OOA, 37 %) was found to be more linked to aged biogenic sources. Equivalent black carbon (eBC), measured by a multi-angle absorption photometer (MAAP) represented 10 % of the total particulate matter (PM). The eBC was clearly associated with HOA, BBOA, and MO-OOA factors (all together R2=0.83). Therefore, eBC's contribution to each factor was achieved using a multi-linear regression model. More than half of the eBC (52 %) was associated with long-range transport (i.e., MO-OOA), whereas liquid fuel eBC (35 %) and biomass burning eBC (13 %) were associated with local emissions, leading to a complete apportionment of the carbonaceous aerosol. The separation between local and transported eBC was well supported by the mass size distribution of elemental carbon (EC) from Berner impactor samples. Air masses with the strongest marine influence, based on back trajectory analysis, corresponded with a low particle mass concentration (6.4–7.5 µg m−3) and organic fraction (≈30 %). However, they also had the largest contribution of primary OA (HOA ≈ 4 % and BBOA 15 %–20 %), which was associated with local emissions. Continental air masses had the highest mass concentration (11.4–12.6 µg m−3), and a larger fraction of oxygenated OA (≈45 %) indicated highly processed OA. The present results emphasize the key role played by long-range transport processes not only in the OA fraction but also in the eBC mass concentration and the importance of improving our knowledge on the identification of eBC sources.

Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements on aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation; however, they are still scarce. In this study, more than 4-year aerosol comprehensive measurements were utilized at the central European research station Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving prediction. The overall characteristics of aerosol particle activation at Melpitz are first summarized. For supersaturation (SS) levels of 0.1 %, 0.2 %, 0.3 %, 0.5 %, and 0.7 %, the mean cloud condensation nuclei (CCN) number concentration (NCCN) increases with the increase of SS from 513 to 2477 cm-3, which represents 11 % to 52 % of the total particle number concentration with diameter ranging from 10 to 800 nm, while the hygroscopicity factor (k) and the critical diameter (Dc) decrease from 0.28±0.08 (mean value ± one standard deviation) to 0.20±0.09 and from 177±19 to 54±8 nm, respectively. Aerosol particle activation is highly variable across seasons, especially at low SS conditions. At SS = 0.1 %, the seasonal mean NCCN is 681 cm-3 in winter, which is almost twice higher than the summer value (347 cm-3); the seasonal mean activation ratio (AR) in winter (0.18) is three times higher than the summer one. Subsequently, size dependency of both k and the state of mixing were investigated. As the particle diameter (Dp) increases, k increases at Dp of ~40 to 100 nm and almost stays constant at Dp of 100 to 200 nm, whereas the degree of the external mixture keeps decreasing at Dp of ~40 to 200 nm. The relationships of k vs. Dp and mixture degree vs. Dp were both fitted well by the power-law function for each season. Finally, we recommend applying the k - Dp power-law fit for NCCN prediction, which can narrow down the median uncertainty within 10 % for different SS conditions and seasons at Melpitz; it also could be applied to predict NCCN at other rural and continental regions with a similar aerosol background. Additionally, the mean k value over Dp of 100 to 200 nm also works well on the NCCN prediction when SS is less than 0.2 %.

The airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as a potential pandemic challenge, especially in poorly ventilated indoor environments, such as certain hospitals, schools, public buildings, and transports. The impacts of meteorological parameters (temperature and humidity) and physical property (droplet size) on the airborne transmission of coronavirus in indoor settings have been previously investigated. However, the impacts of chemical properties of viral droplets and aerosol particles (i.e., chemical composition and acidity (pH)) on viability and indoor transmission of coronavirus remain largely unknown. Recent studies suggest high organic content (proteins) in viral droplets and aerosol particles supports prolonged survival of the virus by forming a glassy gel-type structure that restricts the virus inactivation process under low relative humidity (RH). In addition, the virus survival was found at neutral pH, and inactivation was observed to be best at low (10) values (enveloped bacteriophage Phi6). Due to limited available information, this article illustrates an urgent need to research the impact of chemical properties of exhaled viral particles on virus viability. This will improve our fundamental understanding of indoor viral airborne transmission mechanisms.

In aerosol science, there is an increasing interest to perform mobile measurements to obtain number size distribution of ultrafine particles (UFP), using portable instruments based on unipolar charging and size segregation by electrical particle mobility. Applications of such measurements range from ambient and indoor aerosol studies to source identification in work environments. However, knowledge on the actual measurement uncertainties of these portable instruments under various conditions has been limited. This investigation presents results from an intercomparison workshop conducted at the World Calibration Center for Aerosol Physics (WCCAP) in Leipzig, Germany, in January 2020. Manufacturers and users were invited to have their portable instruments tested and compared against reference instrumentation for particle number size distributions (PNSD) and total particle number concentration (PNC). In particular, the performances and uncertainties of the NanoScan SMPS (Scanning Mobility Particle Sizer) Model 3910 (TSI Inc.) and the Mini Wide Range Aerosol Spectrometer (WRAS) Model 1371 (Grimm Aerosol Technik) were investigated extensively against the WCCAP Mobility Particle Size Spectrometers (MPSS) and Condensation Particle Counters (CPC). A total of 11 TSI NanoScan SMPS and 4 GRIMM Mini WRAS instruments were characterized for ambient aerosols as well as lab-generated aerosols. The workshop results affirm that the portable instruments must be serviced and calibrated annually or prior field studies to provide measurements within the given uncertainties. It should be noted that users should carry out timely service, maintenance and calibration of portable instruments at their facilities. During initial inspection, non-serviced NanoScan SMPS instruments overestimated a dominant ultrafine aerosol mode by 120 % at around 80 nm. Maintenance and servicing improved the performance. Overall, the performance of NanoScan SMPS instruments improved for the ultrafine aerosol mode while the PNC in the fine aerosol mode still overestimated by up to 80 %. The latter effect seems to be systematically related to the unipolar charging of particles, and the reduced sensitivity of electrical particle mobility with increasing particle size above 200 nm. Due to shift in the second mode of bimodal distribution, particles are overcounted around 100 nm. With regard to the integral PNC, some of the NanoScan SMPS found to be in good agreement (i.e. within 20 %) compared to the reference CPC. In addition, a reasonably good unit-to-unit agreement within ±20 % was found for NanoScan SMPS instruments. The Mini WRAS instruments, after proper cleaning and servicing, provided improved results within ±15 % deviation in PNC in the ultrafine aerosol mode. Overall, most of the GRIMM Mini WRAS instruments (operating with software version 10.0) agrees well with PNC (i.e. 10–50 %) when the ultrafine mode was dominant. Conversely, PNC of the fine aerosol mode was systematically underestimated by 60 % above 100 nm. Except for one instrument, the integral PNC of the GRIMM Mini WRAS spectrometers were within an uncertainty range of ±20 % compared to the reference CPC. Additionally, it is important for users to note that the Mini WRAS performed significantly better when using software version 10.0 compared to version 8.2. The workshop results suggest that despite the above-mentioned uncertainties, these portable instruments are suited for mobile ultrafine particle measurements to detect relative differences in the PNSD such as source apportionment studies of ultrafine particles at work places or outdoors near sources.

Background Exposure to air pollutants is one of the major environmental health risks faced by populations globally. Information about inhaled particle deposition dose is crucial in establishing the dose–response function for assessing health-related effects due to exposure to air pollution. Objective This study aims to quantify the respiratory tract deposition (RTD) of equivalent black carbon (BC) particles in healthy young adults during a real-world commuting scenario, analyze factors affecting RTD of BC, and provide key parameters for the assessment of RTD. Methods A novel in situ method was applied to experimentally determine the RTD of BC particles among subjects in the highly polluted megacity of Metro Manila, Philippines. Exposure measurements were made for 40 volunteers during public transport and walking. Results The observed BC exposure concentration was up to 17-times higher than in developed regions. The deposition dose rate (DDR) of BC was up to 3 times higher during commute inside a public transport compared to walking (11.6 versus 4.4 μg hr−1, respectively). This is twice higher than reported in similar studies. The average BC mass deposition fraction (DF) was found to be 43 ± 16%, which can in large be described by individual factors and does not depend on gender. Conclusions Commuting by open-sided public transport, commonly used in developing regions, poses a significant health risk due to acquiring extremely high doses of carcinogenic traffic-related pollutants. There is an urgent need to drastically update air pollution mitigation strategies for reduction of dangerously high emissions of BC in urban setting in developing regions. The presented mobile measurement set-up to determine respiratory tract deposition dose is a practical and cost-effective tool that can be used to investigate respiratory deposition in challenging environments.

There is a gap between the need for city-wide air-quality simulations considering the intra-urban variability and mircoscale dispersion features and the computational capacities that conventional urban microscale models require. This gap can be bridged by targeting model applications on the gray zone situated between the mesoscale and large-eddy scale. The urban dispersion model CAIRDIO is a new contribution to the class of computational-fluid dynamics models operating in this scale range. It uses a diffuse-obstacle boundary method to represent buildings as physical obstacles at gray-zone resolutions in the order of tens of meters. The main objective of this approach is to find an acceptable compromise between computationally inexpensive grid sizes for spatially comprehensive applications and the required accuracy in the description of building and boundary-layer effects. In this paper, CAIRDIO is applied on the simulation of black carbon and particulate matter dispersion for an entire mid-size city using a uniform horizontal grid spacing of 40 m. For model evaluation, measurements from five operational air monitoring stations representative for the urban background and high-traffic roads are used. The comparison also includes the mesoscale host simulation, which provides the boundary conditions. The measurements show a dominant influence of the mixing layer evolution at background sites, and therefore both the mesoscale and large-eddy simulation (LES) results are in good agreement with the observed air pollution levels. In contrast, at the high-traffic sites the proximity to emissions and the interactions with the building environment lead to a significantly amplified diurnal variability in pollutant concentrations. These urban road conditions can only be reasonably well represented by CAIRDIO while the meosocale simulation indiscriminately reproduces a typical urban-background profile, resulting in a large positive model bias. Remaining model discrepancies are further addressed by a grid-spacing sensitivity study using offline-nested refined domains. The results show that modeled peak concentrations within street canyons can be further improved by decreasing the horizontal grid spacing down to 10 m, but not beyond. Obviously, the default grid spacing of 40 m is too coarse to represent the specific environment within narrow street canyons. The accuracy gains from the grid refinements are still only modest compared to the remaining model error, which to a large extent can be attributed to uncertainties in the emissions. Finally, the study shows that the proposed gray-scale modeling is a promising downscaling approach for urban air-quality applications. The results, however, also show that aspects other than the actual resolution of flow patterns and numerical effects can determine the simulations at the urban microscale.

The “Carbonaceous Aerosol in Rome and Environs” (CARE) experiment took place at a Mediterranean urban background site in Rome (Italy) deploying a variety of instrumentation to assess aerosol physical-chemical and optical properties with high-time resolution (from 1 min to 2 h). In this study, aerosol optical properties, chemical composition, and size distribution data were examined with a focus on the analysis of several intensive optical properties obtained from multi-wavelength measurements of aerosol scattering and absorption coefficients. The spectral behaviour of several quantities related to both aerosol composition and size was explored, analysing their high-time resolved temporal patterns and combining them in order to extract the maximum information from all the available data. A methodology to separate aerosol types using optical data only is here proposed and applied to an urban area characterised by a complex mixture of particles. A key is given to correctly disentangle cases that could not be distinguished observing only one or few parameters, but that can be clearly separated using a suitable ensemble of optical properties. The SSCAAE, i.e. the wavelength dependence of the Single Scattering co-albedo 1-SSA (where SSA is the Single Scattering Albedo) - that efficiently responds to both aerosol size and chemical composition – resulted to be the best optical intensive parameter to look at for the discrimination between episodes characterised by specific aerosol types (e.g. sea salt, Saharan dust) and more mixed conditions dominated by local emissions. However, this study also highlighted that it is necessary to combine temporal patterns of different optical parameters to robustly associate SSCAAE features to specific aerosol types. In addition, the complete chemical speciation and the high-time resolved size distribution were used to confirm the aerosol types identified via a combination of aerosol optical properties. Look-up tables with most suitable ranges of values for optical variables were produced; therefore, these pieces of information can be used at the same site or at locations with similar features to quickly identify the occurrence of aerosol episodes. Graphical frameworks (both from the literature and newly designed) are also proposed; for each scheme features, advantages, and limitations are discussed.