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The aerosol size distribution is a crucial metric for evaluating aerosol optical characteristics and determines the direct and indirect radiative forcings of aerosols. Traditional methods for inversion of aerosol size distribution often suffer from ambiguities and limitations. To address these shortcomings, this paper introduces a method for inferring aerosol volume size distribution utilizing an improved Lévy flight and chaotic sparrow search algorithm (ILCSSA). The algorithm incorporates Circle chaotic mapping onto the basic Sparrow Search Algorithm (SSA) to obtain a high-quality initial population and employs a Lévy flight strategy to enhance population diversity. Additionally, the process of updating the population's positions is optimized to improve algorithm accuracy. To validate the feasibility of the proposed method, the measured aerosol optical depth (AOD) data obtained from a Precision Solar Radiometer (PSR) sun photometer in Shouxian are utilized and a series of comparisons were conducted among the Sparrow Search Algorithm, Standard Particle Swarm Algorithm, Improved Particle Swarm Algorithm, and Spider Wasp Optimization Algorithm. The results demonstrate a significant performance advantage for the ILCSSA, evidenced by an average reduction of 50%in Sum of Squared Errors (SSE) and 36% in Root Mean Squared Error (RMSE) when compared to the other four algorithms. Additionally, the AOD obtained by ILCSSA had a correlation coefficient of 0.9748 with the original AOD data. Furthermore, we analyzed the aerosol volume size distribution in Shouxian under conditions of good air quality, moderate pollution, and mild pollution. The proposed method holds significant reference value in the field of aerosol volume spectrum inversion. [ABSTRACT FROM AUTHOR]

Aerosol measurements during the DOE ARM Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign were used to quantify the differences between clean and smoky cloud condensation nuclei (CCN) budgets. Accumulation‐mode particles accounted for ∼70% of CCN at supersaturations <0.3% in clean and smoky conditions. Aitken‐mode particles contributed <20% and sea‐spray‐mode particles <10% at supersaturations <0.3%, but at supersaturations >0.3% Aitken particles contributions increased to 30%–40% of clean CCN. For clean conditions, the Hoppel minimum diameter was correlated to the accumulation‐mode number concentration, indicating aerosol‐correlated cloud activation was controlling the lower diameter cutoff for which particles serve as CCN. For smoky conditions, the contributions of Aitken particles increase and the correlation of cloud activation to accumulation‐mode particles is masked by the lower‐hygroscopicity smoke. These results provide the first multi‐month in situ quantitative constraints on the role of aerosol number size distributions in controlling cloud activation in the tropical Atlantic boundary layer. Plain Language Summary: Tiny airborne particles provide the "seeds" on which cloud droplets form, and clouds are in turn important for regulating climate around the world. The small number of measurements characterizing these particles in conditions that are not affected by man‐made emissions make it difficult to represent these cloud processes in computer models that compare current climate to pre‐industrial conditions. Aerosol measurements collected for 17 months on an isolated island in the tropical Atlantic Ocean show how the size and number of particles affect cloud characteristics. The long timescale and wide range from very clean to very smoky aerosol conditions revealed not only differences in the particles that activate in clouds but also in the mechanisms that control that droplet formation process. In clean air, the size required to form a cloud droplet is influenced by the number of particles, as well as how quickly particles take up water during growth in cloud. However, in smoky air, the larger number and size of particles mean that cloud activation processes are less affected by the number of particles that take up water. Key Points: Clean cloud condensation nuclei (CCN) at <0.3% supersaturation were ∼70% accumulation, <10% sea spray, and <20% Aitken mode particlesHoppel minimum diameters correlated to accumulation‐mode particles showing aerosol‐correlated activation for clean conditions (<400 cm−3)Smoky accumulation‐mode particles were 30 nm larger and had 15%–30% more CCN, which dampened correlations to cloud activation [ABSTRACT FROM AUTHOR]

Abstract Aerosol measurements during the DOE ARM Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign were used to quantify the differences between clean and smoky cloud condensation nuclei (CCN) budgets. Accumulation‐mode particles accounted for ∼70% of CCN at supersaturations 0.3% Aitken particles contributions increased to 30%–40% of clean CCN. For clean conditions, the Hoppel minimum diameter was correlated to the accumulation‐mode number concentration, indicating aerosol‐correlated cloud activation was controlling the lower diameter cutoff for which particles serve as CCN. For smoky conditions, the contributions of Aitken particles increase and the correlation of cloud activation to accumulation‐mode particles is masked by the lower‐hygroscopicity smoke. These results provide the first multi‐month in situ quantitative constraints on the role of aerosol number size distributions in controlling cloud activation in the tropical Atlantic boundary layer.

In the recent decades, advanced instrumentation has been developed to measure the atmospheric aerosol's physical-chemical properties with increased temporal detail and size resolution. The characterization of the atmospheric aerosol is now provided at a more detailed level. Nevertheless, it is still challenging to maximize the exploitation of such detailed information in receptor models to perform more reliable source apportionment studies. Indeed, detailed time- and size-resolved sampling can, in principle, provide additional information to better identify specific emission sources and/or atmospheric processes, but an associated complete chemical characterization is often lacking, or is provided at low time resolution by PM X samples. To this aim, a completely novel, multi-time, multi-size resolution positive matrix factorization (MTMS-PMF) is presented. This cutting-edge receptor model is an expansion of the widely used PMF and allows the analysis of data measured at different time resolutions in multiple size classes. As output, it provides size-segregated chemical profiles and factor temporal contributions retrieved at the highest temporal resolution available in the dataset. The MTMS-PMF was implemented in a script for the Multilinear Engine ME-2 program and successfully tested on a large dataset collected in the Po Valley (Ferrara, Italy) during years 2008–2018. The dataset included aerosol chemical species measured on multistage impactor samples (8 size classes) at a low time resolution of about 1–3 weeks and daily PM 10 samples covering almost the same sampling periods. The outputs retrieved at the higher time and size resolutions greatly strengthened the source-to-factor assignment. Moreover, the possibility to acquire information about the size distributions of atmospheric aerosol emitted by a variety of sources is highly valuable for impact assessment and for developing focused mitigation strategies aimed at addressing specific negative aerosol effects. [Display omitted] • Combining traditional and advanced atmospheric aerosol data from different sampler types in receptor models is challenging. • An expansion of the positive matrix factorization is proposed to take advantage of data measured at different time and size resolutions. • This model applies to many datasets, providing enhanced source identification and key information for mitigation strategies. [ABSTRACT FROM AUTHOR]

Chemical composition of aerosols is of great concern in the Arctic because of its great influence on climate. In this communication, we report the physico-chemical properties of size-separated aerosol data archived at Gruvebadet lab in Ny-Ålesund (78.55°S, 11.55°E) as a part of the Indian Arctic Mission over the station ''Himadri'' in 2010. The results reveal that the mass-size distribution (MSD) of aerosol composition exhibits tri-modal distribution with coarse-mode (62%), fine-mode (32%) and weak nucleation-mode (6%) indicating dominance of natural sources over the study region. MSD of chemical components showed a significant contribution to coarse-mode particles for Ca2+, Mg2+, Na+ and Cl−; fine-mode particles for SO42−, NO3−, NH4+ and K+. The marine sources contributed maximum for SO42− (89%) and Mg2+ (44%) in the coarse fraction, and in the fine fraction, 31% to SO42− and 86% to Mg2+. Non-marine sources were major contributors (80 to 95%) in both mode fractions for Ca2+and K+. The estimated aerosol radiative forcing in the atmosphere of ∼3.21 W/m2 could be attributed to the loading of black carbon aerosols (62%) over the site. The backward trajectories show air masses from Canada and Greenland travelling from 6000 m elevation, bringing the pollutants to Ny-Ålesund and lower altitudes; the oceanic region within Arctic circle contributes more.

Size-resolved composition of atmospheric aerosol particles during winter (19 December 2014 to 13 January 2015) in the San Joaquin Valley at Fresno and during summer (4 to 28 July 2015) in the Southern California Air Basin at Fontana were measured by aerosol mass spectrometer, Fourier transform infrared spectrometer, single particle soot photometer, and scanning electrical mobility sizer. The Fresno study had low-fog and high-fog winter conditions, and residential burning was a frequent contributor to evening emissions. Fireworks during Fourth of July celebrations characterized the start of the Fontana study; the remaining days were categorized as nonfirework days and were mostly affected by traffic emissions. Fresno had particle distributions with number mode diameters of 70–150 nm, and Fontana had 30–50-nm diameters. The nonrefractory organic mass mode diameters were also larger at Fresno (250–380 nm in dry mobility diameter) than at Fontana (130–150 nm, 280 nm in dry mobility diameter) as were refractory black carbon particles (Fresno: 80–180 nm; Fontana: 80–100 nm in dry volume equivalent diameter). The size dependence of organic contributions to particle mass indicated that condensation or other surface-limited processes contributed oxidized organic fractions to aerosol mass in Fontana but that volume-limited aqueous reactions produced organic mass on both low-fog and high-fog days in Fresno. Linear regression analysis of organic aerosol sources with size-resolved particle volume at different times of day also showed that residential burning-related particles increased from 70–160 nm in the evening (18:00 to 23:59) to 150–260 nm at night (00:00 to 05:59) on low-fog days.

Following the Hunga Tonga eruption (20.6°S, 175.4°W, mid‐January 2022), we present a balloon‐borne characterization of the stratospheric aerosol plume one week after its injection (on 23 and 26 January 2022, La Réunion island at 21.1°S, 55.3°E). Satellite observations show that flight (a) took place during the overpass of a denser plume of sulfate aerosols (SA) compared to a more diluted plume during flight. (b) Observations show that the sampled plumes (at around 22, 25 and 19 km altitude, respectively) consist exclusively of very small particles (with radius <1 µm). Particles with radii between 0.5 and 1.0 µm show optically transparent features pointing to predominant SA. Particles with radii below 0.5 µm are partly absorbing, which could point to small sulfate coated ash particles, a feature not identified with space‐borne observations. This shows that in situ observations are necessary to fully characterize the microphysical properties of the plumes tracked by space‐borne instruments. Plain Language Summary: The Hunga Tonga‐Hunga Ha'apai volcano (at 20.6°S, 175.4°W) erupted on 13 and 15 January 2022 with injection of gases and aerosols up to 55 km altitude. Here, we present a study based on in situ aerosol observations on weather balloons on La Réunion (21.1°S, 55.3°E) within the injected Hunga Tonga aerosol plume one week after the eruption (23 and 26 January 2022). With respective satellite observations, we show that the first measurement flight took place during the overpass of a denser aerosol plume compared to the second flight. We find that the plume exhibits only small particles <1 μm, mainly consisting of sulfate aerosols (for particles between 0.5 and 1 μm in size) and an absorbing component for very small particles (<0.5 μm), possibly pointing to small ash particles coated by sulfur. This letter "absorbing" feature is a unique contribution brought by in situ measurements that fills a gap left by space‐borne instruments. Key Points: Predominant particle size range of <1 μm within the stratospheric aerosol plume of the Hunga Tonga eruptionOptically absorbing particles within the plume for particles <0.5 μm point to fractured, very small ash particlesMostly optically semi‐transparent particles, for particle sizes between 0.5 and 1.0 μm result from small sulfur coated ash particles [ABSTRACT FROM AUTHOR]

Accurate information about aerosol particle size distribution and its variation under different meteorological conditions are essential for reducing uncertainties related to aerosol-cloud-climate interaction processes. New particle formation (NPF) and the coagulation significantly affect the aerosol size distribution. Here we study the monthly and seasonal variability of aerosol particle size distribution at Delhi from December 2011 to January 2013. Analysis of aerosol particle size distribution using WRAS-GRIMM reveals that aerosol particle number concentration is highest during the post monsoon season owing to the effect of transported crop residue and biomass burning aerosols. Diurnal variations in number concentration show a bimodal pattern with two Aitken mode peaks in all the seasons. Monthly volume size distribution also shows bi-modal distribution with distinct coarse and fine modes. NPF events are observed less frequently in Delhi. Out of 222 days of WRAS data, only 17 NPF events have been observed, with higher NPF frequency during summer season. Growth rate of the nucleation mode of NPF events vary in the range 1.88–21.66 nm/h with a mean value of ∼8.45 ± 5.73 nm/h. It is found that during NPF events the Aitken and nucleation mode particles contribute more to the number concentration. Simultaneous measurement of UV flux and particulate matter (PM10 and PM2.5) have also been done along with particle number size distribution measurement to understand the possible mechanisms for NPF events over the study location.

In air quality research, often only particle mass concentrations as indicators of aerosol particles are considered. However, the mass concentrations do not provide sufficient information to convey the full story of fractionated size distribution, which are able to deposit differently on respiratory system and cause various harm. Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. From the raw data the ambient size distribution is determined utilising a suite of inversion algorithms. However, the inversion problem is quite often ill-posed and challenging to invert. Due to the instrumental insufficiency and inversion limitations, models for fractionated particle size distribution are of great significance to fill the missing gaps or negative values. The study at hand involves a merged particle size distribution, from a scanning mobility particle sizer (NanoSMPS) and an optical particle sizer (OPS) covering the aerosol size distributions from 0.01 to 0.42 µm (electrical mobility equivalent size) and 0.3 µm to 10 µm (optical equivalent size) and meteorological parameters collected at an urban background region in Amman, Jordan in the period of 1st Aug 2016–31st July 2017. We develop and evaluate feed-forward neural network (FFNN) models to estimate number concentrations at particular size bin with (1) meteorological parameters, (2) number concentration at other size bins, and (3) both of the above as input variables. Two layers with 10–15 neurons are found to be the optimal option. Lower model performance is observed at the lower edge (0.01< Dp< 0.02 µm), the mid-range region (0.15< Dp< 0.5 µm) and the upper edge (6< Dp< 10 µm). For the edges at both ends, the number of neighbouring size bins is limited and the detection efficiency by the corresponding instruments is lower compared to the other size bins. A distinct performance drop over the overlapping mid-range region is due to the deficiency of a merging algorithm. Another plausible reason for the poorer performance for finer particles is that they are more effectively removed from the atmosphere compared to the coarser particles so that the relationships between the input variables and the small particles is more dynamic. An observable overestimation is also found in early morning for ultrafine particles followed by a distinct underestimation before midday. In the winter, due to a possible sensor drift and interference artefacts, the model performance is not as good as the other seasons. The model by meteorological parameters using 5-min data (R² = 0.22– 0.58) shows poorer results than data with longer time resolution (R² = 0.66–0.77). The model by the number concentration at the other size bins can serve as an alternative way to replace negative number in size distribution raw dataset thanks to its high accuracy and reliability (R² = 0.97–1). This negative numbers filling method can maintain a symmetric distribution of errors. [ABSTRACT FROM AUTHOR]

Abstract Aerosol is a key factor in the study of interactions between light and radiation. In coastal environments, the diversity and complexity of aerosol components make it difficult to accurately determine their microphysical and optical properties. In this paper, the analysis focuses on the aerosol size distribution (ASD) prediction in the coasts of the South China Sea (SCS, Maoming) and the Yellow Sea (YS, Qingdao). Due to large differences in spatial scale with respect to geographical and meteorological conditions, ASD in Maoming and Qingdao showed large differences. On the basis of Navy Aerosol Model (NAM) and Piazzola et al.'s models, combined with the observation data of Maoming and Qingdao, a coastal aerosol model (CAM) was developed to predict ASD for Chinese coastal environment. The aerosol concentration is calculated by the function of fetch and wind speed. Although the aerosol distributions at the two sites are quite different, the CAM is found to be applicable to both sites. Furthermore, the CAM was used in predicting the ASDs in the SCS against the research ship Shenkuo cruise data. The model results were in agreement with the measured values in coastal zone. The model presented in this work would be a useful tool to model ASDs in Chinese coastal seas.

Mineral dust aerosols are composed of a complex mixture of silicates, carbonates, oxides, and sulfates. The minerals’ chemical composition and size distribution are vital parameters to evaluate dust environmental impacts. However, the quantification of minerals remains a challenge due to the sparse in situ measurements of dust samples. Here we derive the size-resolved mineralogical composition of airborne dust aerosols from MODIS (Terra and Aqua) satellite-acquired optical measurements and compare it with chemically analyzed elemental (Al, Fe, Ca, Mg) concentrations of aerosols for PM2.5 and PM10 from Chonburi, Chiang Rai, and Bangkok in Thailand, and from Singapore. MODIS-derived mineral retrievals exhibited high correlations with elemental concentrations with R2 ≥ 0.84 for PM2.5 and ≥0.96 for PM10. High mineral dust activity was detected in the vicinity of biomass-burning areas with gypsum and calcite exhibiting tracer characteristics of combustion. The spatiotemporal pattern of the MODIS-derived minerals matched with Ozone Monitoring Instrument (OMI)-derived dust, sulfates, and carbonaceous aerosols, indicating the model’s consistency. Variation in aerosol loading by ±90% led to deviation in the mineral concentration by

Aerosol is a key factor in the study of interactions between light and radiation. In coastal environments, the diversity and complexity of aerosol components make it difficult to accurately determine their microphysical and optical properties. In this paper, the analysis focuses on the aerosol size distribution (ASD) prediction in the coasts of the South China Sea (SCS, Maoming) and the Yellow Sea (YS, Qingdao). Due to large differences in spatial scale with respect to geographical and meteorological conditions, ASD in Maoming and Qingdao showed large differences. On the basis of Navy Aerosol Model (NAM) and Piazzola et al.'s models, combined with the observation data of Maoming and Qingdao, a coastal aerosol model (CAM) was developed to predict ASD for Chinese coastal environment. The aerosol concentration is calculated by the function of fetch and wind speed. Although the aerosol distributions at the two sites are quite different, the CAM is found to be applicable to both sites. Furthermore, the CAM was used in predicting the ASDs in the SCS against the research ship Shenkuo cruise data. The model results were in agreement with the measured values in coastal zone. The model presented in this work would be a useful tool to model ASDs in Chinese coastal seas. Plain Language Summary: This study focuses on the aerosol size distribution (ASD) prediction in the coasts of the South China Sea (SCS, Maoming) and the Yellow Sea (YS, Qingdao). Maoming and Qingdao showed large differences in the ASD due to the differences in geographical environment, climatic conditions. Based on previous studies and observation data, a coastal aerosol model (CAM) was developed to predict ASD for Chinese coastal environment. A variable, that is, the fetch, was introduced in CAM, instead of the dimensionless air mass parameter (AMP) used in the existed prediction models, to describe the coast effect on the ASD. Although the aerosol distributions at the two sites are quite different, experimental validation results both showed that the CAM was in reasonable agreement with the measured data. ASDs predictions compared with the SCS measurements (from the research ship Shenkuo cruise) also showed the good performance of CAM in coastal zones. Key Points: A coastal aerosol model was developed to predict the aerosol size distribution for Chinese coastal environmentBased on the observed dataset, aerosol concentrations can be modeled by the function of fetch and wind speedThe coastal aerosol distributions are related to different kinds of coastal environments [ABSTRACT FROM AUTHOR]

Despite being recognized as an important part of particulate matter (PM) air pollution and health risk, bioaerosols have not been quantified as extensively as other PM components for establishing PM standards and management strategies. The challenge lies partly in the lack of practical measurement methods. This study evaluated a filter-based, direct-staining fluorescence microscopy (DS-FM) method that may be adapted to routine air quality monitoring for bioaerosol concentration and size distribution. Through testing with bioaerosol standards made of bacterial cells and fungal spores, the method is shown to have precision, accuracy, detection limit, and dynamic range suitable for most ambient environments. DS-FM was demonstrated with PM samples from an arid urban location in Las Vegas, Nevada during the spring allergy season. Detectable bioaerosols ranged from 0.37 to 16 μm in geometric diameter and averaged 0.27 ± 0.23 cm−3 in number concentration with about 2/3 and 1/3 in the fine (≤2.5 μm) and coarse (>2.5 μm) mode, respectively. The bioaerosol mass, estimated from the size distribution and an assumed density, was mainly in the coarse mode and accounted for 17 ± 11% of PM 10 , 20 ± 13% of PM 10-2.5 , and 4 ± 3% of PM 2.5 mass. Rain and high wind speeds appeared to elevate bioaerosol levels. Other advantages of DS-FM include low sample consumption and short turnaround times; a large amount of data can be generated by incorporating the measurement into current long-term air quality networks. Suggestions for using the data to inform bioaerosol origins, contributions, and public health impacts are discussed. Image 1 • Bioaerosol number and size ranges are measured with a filter-based, direct-staining fluorescence microscopy (DS-FM) method. • Tests of DS-FM using bioaeorsol standards show adequate sensitivity, accuracy, and dynamic range for outdoor monitoring. • DS-FM estimates bioaerosol concentrations of 0.1–1.5 cm-3 in Las Vegas, Nevada and accounting for 17±11% of PM 10 mass. • High precipitation and wind speed are found to significantly elevate the ambient bioaerosol levels. [ABSTRACT FROM AUTHOR]

Abstract Measuring aerosol size distributions accurately down to ~1 nm is a key to nucleation studies, and it requires developments and improvements in instruments such as electrical mobility spectrometers in use today. The key factors characterizing the performance of an electrical mobility spectrometer for sub-3 nm particles are discussed in this study. A parameter named as Π is proposed as a figure of merit for the performance of an electrical mobility spectrometer in the sub-3 nm size range instead of the overall detection efficiency. Π includes the overall detection efficiency, the measurement time in each size bin, the aerosol flow rate passing through the detector, and the aerosol-to-sheath flow ratio of the differential mobility analyzer. The particle raw count number recorded by the detector can be estimated using Π at a given aerosol size distribution function, d N /dlog d p. The limit of detection for the spectrometer and the statistical uncertainty of the measured aerosol size distribution can also be readily estimated using Π. In addition to Π , the size resolution of an electrical mobility analyzer is another factor characterizing the systematic errors originated from particle sizing. Four existing electrical mobility spectrometers designed for measuring sub-3 nm aerosol size distributions, including three scanning/differential mobility particle spectrometers and one differential mobility analyzer train, are examined. Their optimal performance is evaluated using Π and the size resolution. For example, the Π value and the size resolution of a diethylene-glycol differential mobility particle spectrometer for 1.5 nm particles are 8.0 × 10−4 cm3 and 5.7, respectively. The corresponding relative uncertainty of the measured size distribution is approximately 9.6% during an atmospheric new particle formation event with a d N /dlog d p of 5 × 105 cm−3. Assuming an adjustable sheath flow rate of the differential mobility analyzer, the optimal size resolution is approximately 5–9 when measuring atmospheric new particle formation events. Highlights • A parameter to characterize the performance of an electrical mobility spectrometer for sub-3 nm particles. • Characterizing the uncertainties using the new parameter and size resolution. • Instructions on reducing the uncertainties in measuring sub-3 nm atmospheric particles. [ABSTRACT FROM AUTHOR]

Abstract Aerosol size distributions and cloud condensation nuclei (CCN) number concentrations were measured in spring 2017 over the Yellow Sea on board the research vessel Gisang 1. The average number concentration of particles larger than 10 nm and CCN at 0.65% supersaturation (S) were 7622 ± 4038 cm−3 and 4821 ± 1763 cm−3, respectively. Characteristics of aerosol size distribution data were analyzed using a positive matrix factorization (PMF) method. It was found that only 6 Factors could explain the aerosol size distribution reasonably well. Factors 1 and 2 indicated nucleation mode particles, Factor 3 indicated Aitken mode particles, and Factors 4, 5, and 6 indicated accumulation mode particles. The concentrations of nucleation and Aitken mode particles showed a clear wind direction dependence; high under westerly winds due to the high concentrations of particles and precursor gases in eastern China. Meanwhile, the concentration of larger particles and CCN showed no significant wind direction dependence. Aerosol size distribution was also significantly influenced by meteorology. Small particles were predominant during clear days. In contrast during mist or fog days, the aerosol size distribution shifted to larger sizes. A CCN closure experiment was conducted using results of the PMF analysis. The assumption of internally mixed particles led to overestimation of predicted CCN concentrations but agreement was significantly better when externally mixed particles were considered. The logarithmic curve fit of N CCN (S) = 4825 ∗ log S + 4933 was found to very well explain measured CCN concentrations at a few S over the Yellow Sea, and therefore is recommended as input CCN spectral data for numerical models that explicitly treat CCN activation. Highlights • Aerosol size dist. and CCN conc. measured over the Yellow Sea onboard a ship were analyzed with the PMF analysis method. • Aerosol size dist. were significantly influenced by meteorological conditions. • CCN closure experiment implied that some portion of the aerosols over the Yellow Sea were externally mixed. • A fitted full CCN spectrum was proposed based on the CCN conc. measured at several supersaturation over the Yellow Sea. [ABSTRACT FROM AUTHOR]

Accurate representation of atmospheric aerosol properties is a long-standing problem in atmospheric research. Modern pilotless aerial systems provide a new platform for atmospheric in situ measurement. However, small airborne platforms require miniaturized instrumentation due to apparent size, power, and weight limitations. A Portable Optical Particle Spectrometer (POPS) is an emerged instrument to measure ambient aerosol size distribution with high time and size resolution, designed for deployment on a small unmanned aerial system (UAS) or tethered balloon system (TBS) platforms. This study evaluates the performance of a POPS with an upgraded laser heater and additional temperature sensors in the aerosol pathway. POPS maintains its performance under different environmental conditions as long as the laser temperature remains above 25 °C and the aerosol flow temperature inside the optical chamber is 15 °C higher than the ambient temperature. The comparison between POPS and an Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) suggests that the coincidence error is less than 25% when the number concentration is less than 4000 cm−3. The size distributions measured by both of them remained unaffected up to 15,000 cm−3. While both instruments’ sizing accuracy is affected by the aerosol chemical composition and morphology, the influence is more profound on the POPS.

Nitrate has become the most important hydrophilic chemical component in PM 2.5 during serious air pollution periods in urban areas of the Pearl River Delta (PRD) region of south China, but there is a lack of fully understanding of its formation mechanisms and controlling factors, especially during daytime nitrate episodes. To fill the knowledge gap, water-soluble inorganic ions in PM 2.5 and trace gases including SO 2 , HNO 3 , NH 3 , NOx and O 3 , particle size distribution, vertical profile of aerosol backscatter density, and ground-level and vertical profiles of key meteorological variables were simultaneously measured at high time resolution in urban Guangzhou of the PRD. The remarkably enhanced nitrate mass concentrations observed at the surface-level during daytime were identified to be caused by strong boundary-layer turbulent mixing of residual aerosols produced from evaporation of low-level shallow stratocumulus clouds. This finding may have important implications on the sources of secondary inorganic aerosols in this and other similar cloudy regions. [ABSTRACT FROM AUTHOR]

We carried out field measurements of aerosols in Lhasa, a major city in the Tibetan Plateau that has been experiencing fast urbanization and industrialization. Aerosol number size distribution was continuously measured using an optical particle size spectrometer near the center of Lhasa city during the Asian summer monsoon season in 2016. The mass concentration of fine particles was modulated by boundary layer dynamics, with an average of 11 μg m −3 and the high values exceeding 50 μg m −3 during religious holidays. Daytime high concentration coincided with the religious burning of biomass and incense in the temples during morning hours, which produced heavy smoke. Factor analysis revealed a factor that likely represented religious burning. The factor contributed 34% of the campaign-average fine particle mass and the contribution reached up to 80% during religious holidays. The mass size distribution of aerosols produced from religious burnings peaked at ∼500 nm, indicating that these particles could efficiently decrease visibility and promote health risk. Because of its significance, our results suggest that further studies of religious burning, a currently under-studied source, are needed in the Tibetan Plateau and in other regions of the world where religious burnings are frequently practiced. [ABSTRACT FROM AUTHOR]

In this paper, we combined a Potential Source Contribution Function (PSCF) analysis of daily chemical aerosol composition data with hourly aerosol size distributions with the aim to disentangle the major source areas during a complex and fast modulating advection event impacting on Central Italy in 2013. Chemical data include an ample set of metals obtained by Proton Induced X-ray Emission (PIXE), main soluble ions from ionic chromatography and elemental and organic carbon (EC, OC) obtained by thermo-optical measurements. Size distributions have been recorded with an optical particle counter for eight calibrated size classes in the 0.27–10 μm range. We demonstrated the usefulness of the approach by the positive identification of two very different source areas impacting during the transport event. In particular, biomass burning from Eastern Europe and desert dust from Sahara sources have been discriminated based on both chemistry and size distribution time evolution. Hourly BT provided the best results in comparison to 6 h or 24 h based calculations. [ABSTRACT FROM AUTHOR]

In this work, a comprehensive characterisation and source apportionment of size-segregated aerosol collected using a multistage cascade impactor was performed. The samples were collected during wintertime in Milan (Italy), which is located in the Po Valley, one of the main pollution hot-spot areas in Europe. For every sampling, size-segregated mass concentration, elemental and ionic composition, and levoglucosan concentration were determined. Size-segregated data were inverted using the program MICRON to identify and quantify modal contributions of all the measured components. The detailed chemical characterisation allowed the application of a three-way (3-D) receptor model (implemented using Multilinear Engine) for size-segregated source apportionment and chemical profiles identification. It is noteworthy that - as far as we know - this is the first time that three-way source apportionment is attempted using data of aerosol collected by traditional cascade impactors. Seven factors were identified: wood burning, industry, resuspended dust, regional aerosol, construction works, traffic 1, and traffic 2. Further insights into size-segregated factor profiles suggested that the traffic 1 factor can be associated to diesel vehicles and traffic 2 to gasoline vehicles. The regional aerosol factor resulted to be the main contributor (nearly 50%) to the droplet mode (accumulation sub-mode with modal diameter in the range 0.5–1 μm), whereas the overall contribution from the two factors related to traffic was the most important one in the other size modes (34–41%). The results showed that applying a 3-D receptor model to size-segregated samples allows identifying factors of local and regional origin while receptor modelling on integrated PM fractions usually singles out factors characterised by primary (e.g. industry, traffic, soil dust) and secondary (e.g. ammonium sulphate and nitrate) origin. Furthermore, the results suggested that the information on size-segregated chemical composition in different size classes was exploited by the model to relate primary emissions to rapidly-formed secondary compounds. [ABSTRACT FROM AUTHOR]

Columnar aerosol volume size distributions from March 2012 to February 2013 in Wuhan, China, were investigated with a focus on monthly and seasonal variations in the aerosol optical depths (AODs) and Ångström exponents. AOD is wavelength dependent, and for AOD at, for example, 500 nm, the seasonal averaged AOD value decreased in the order of winter (~0.84), spring (~0.83), summer (~0.76) and autumn (~0.55). The Ångström exponent suggested that the aerosol sizes in summer (~1.22), winter (~1.14), autumn (~1.06) and spring (~0.99) varied from fine to coarse particles. The Ångström exponent and AOD could provide a qualitative evaluation of ASD. Moreover, aerosol size distribution (ASD) was larger in winter than the other three seasons, especially from 1.0 µm to 15 µm due to heavy anthropogenic aerosol and damp climate. The ASD spectral shape showed a bimodal distribution in autumn, winter, and spring, with one peak (0.14) in the coarse mode range. However, there appeared to be a trimodal distribution during summer, with two peaks in the coarse mode, which might be due to the hygroscopic growth of the local particles and the generation of aerosol precursor resulting from the extreme-high temperature and relative humidity.

A Fast Integrated Mobility Spectrometer (FIMS) with a wide dynamic size range has been developed for rapid aerosol size distribution measurements. The design and model evaluation of the FIMS are presented in the preceding paper (Paper I, Wang et al., 2017 ), and this paper focuses on the experimental characterization of the FIMS. Monodisperse aerosol with diameter ranging from 8 to 600 nm was generated using a Differential Mobility Analyzer (DMA), and was measured by the FIMS in parallel with a Condensation Particle Counter (CPC). The mean particle diameter measured by the FIMS is in good agreement with the DMA centroid diameter. Comparison of the particle concentrations measured by the FIMS and CPC indicates the FIMS detection efficiency is essentially 100% for particles with diameters of 8 nm or larger. For particles smaller than 20 nm or larger than 200 nm, FIMS transfer function and mobility resolution can be well represented by the calculated ones based on simulated particle trajectories in the FIMS. For particles between 20 and 200 nm, the FIMS transfer function is boarder than the calculated, likely due to non-ideality of the electric field, including edge effects near the end of the electrode, which are not represented by the 2-D electric field used to simulate particle trajectories. [ABSTRACT FROM AUTHOR]

This study investigated the “roadside-to-ambient” evolution of particle physicochemical and optical properties in typical urban atmospheres of Hong Kong through collection of chemically-resolved PM 2.5 data and PM 2.5 size distribution at a roadside and an ambient site. Roadside particle size distribution showed typical peaks in the nuclei mode (30–40 nm) while ambient measurements peaked in the Aitken mode (50–70 nm), revealing possible condensation and coagulation growth of freshly emitted particles during aging processes. Much higher levels of anthropogenic chemical components, i.e. nitrate, sulfate, ammonium, organic carbon (OC) and elemental carbon (EC), but lower levels of OC/EC and secondary inorganic aerosols (SIA)/EC ratios appeared in roadside than ambient particles. The high OC/EC and SIA/EC ratios in ambient particles implied high contributions from secondary aerosols. Black carbon (BC), a strong light absorbing material, showed large variations in optical properties when mixed with other inorganic and organic components. Particle-bound polycyclic aromatic hydrocarbons ( p -PAHs), an indicator of brown carbon (BrC), showed significant UV-absorbing ability. The average BC and p -PAHs concentrations were 3.8 and 87.6 ng m −3 , respectively, at the roadside, but were only 1.5 and 18.1 ng m −3 at the ambient site, suggesting BC and p -PAHs concentrations heavily driven by traffic emissions. In contrast, PM 2.5 UV light absorption coefficients ( b abs-BrC,370nm ) at the ambient site (4.2 Mm −1 ) and at the roadside site (4.1 Mm −1 ) were similar, emphasizing that particle aging processes enhanced UV light-absorbing properties, a conclusion that was also supported by the finding that the Absorption Ångström coefficient (AAC) value at UV wavelengths (AAC _UV band ) at the ambient site were ∼1.7 times higher than that at the roadside. Both aqueous reaction and photochemically produced secondary organic aerosol (SOA) for ambient aerosols contributed to the peak values of b abs-BrC,370nm in ambient particles at midnight and around noon, highlighting that secondary BrC had different sources and particle aging in the atmosphere affected BrC and BC properties and related aerosol light absorption. [ABSTRACT FROM AUTHOR]

A high number of aerosol particle shrinkage cases (70) have been identified and analyzed from an extensive and representative database of aerosol size distributions obtained between 2009 and 2015 at an urban background site in Madrid (Spain). A descriptive classification based on the process from which the shrinkage began is proposed according which shrinkage events were divided into three groups: (1) NPF + shrinkage (NPF + S) events, (2) aerosol particle growth process + shrinkage (G + S) events, and (3) pure shrinkage (S) events. The largest number of shrinkages corresponded to the S-type followed by NPF + S, while the G + S events were the least frequent group recorded. Duration of shrinkages varied widely from 0.75 to 8.5 h and SR from −1.0 to −11.1 nm h −1 . These processes typically occurred in the afternoon, around 18:00 UTC, caused by two situations: i) a wind speed increase usually associated with a change in the wind direction (over 60% of the observations) and ii) the reduction of photochemical activity at the end of the day. All shrinkages were detected during the warm period, mainly between May and August, when local meteorological conditions (high solar irradiance and temperature and low relative humidity), atmospheric processes (high photochemical activity) and availability of aerosol-forming precursors were favorable for their development. As a consequence of these processes, the particles concentration corresponding to the Aitken mode decreased into the nucleation mode. The accumulation mode did not undergo significant changes during these processes. In some cases, a dilution of the particulate content in the ambient air was observed. This work, goes further than others works dealing with aerosol particles shrinkages, as it incorporates as a main novelty a classification methodology for studying these processes. Moreover, compared to other studies, it is supported by a high and representative number of observations. Thus, this study contributes to get a better understanding of this type of atmospheric aerosol transformations and its features. [ABSTRACT FROM AUTHOR]

A fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics ( Kulkarni & Wang, 2006a, 2006b ; Olfert, Kulkarni, & Wang, 2008 ). However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field ( Wang, 2009 ). This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporating this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. The experimental characterization of the FIMS is presented in an accompanying paper. [ABSTRACT FROM AUTHOR]

The aerosol chemical vapor deposition (ACVD) process has been demonstrated as a promising approach to the single step synthesis of nanostructured metal oxide thin films. Multiple process parameters control the nanostructure morphology and the growth of thin films. This work focuses on utilizing a simulation based approach to understand the role of these parameters in governing the morphology of the thin film. A finite element based computational fluid dynamics model, coupled with a discrete-sectional aerosol model, and a boundary layer diffusion and sintering model has been formulated to predict the evolution of particle size distribution and the morphology of the synthesized nanostructured film. The morphology predicted by the model was validated by experimental observations. The model enables scale up and wider application of the ACVD process and can be extended to other gas phase deposition systems. [ABSTRACT FROM AUTHOR]

In this study, the Ångstrom exponent for polydispersed aerosol during dynamic processes was investigated. Log-normal aerosol size distribution was assumed, and a sensitivity analysis of the Ångstrom exponent with regards the coagulation and condensation process was performed. The Ångstrom exponent is expected to decrease because of the particle growth due to coagulation and condensation. However, it is difficult to quantify the degree of change. In order to understand quantitatively the change in the Ångstrom exponent during coagulation and condensation, different real and imaginary parts of the refractive index were considered. The results show that the Ångstrom exponent is sensitive to changes in size distribution and refractive index. The total number concentration decreases and the geometric mean diameter of aerosols increase during coagulation. On the while, the geometric standard deviation approaches monodispersed size distribution during the condensation process, and this change in size distribution affects the Ångstrom exponent. The degree of change in the Ångstrom exponent depends on the refractive index and initial size distribution, and the size parameter changes with the Ångstrom exponent for a given refractive index or chemical composition; this indicates that the size distribution plays an important role in determining the Ångstrom exponent as well as the chemical composition. Subsequently, this study shows how the Ångstrom exponent changes quantitatively during the aerosol dynamics processes for a log-normal aerosol size distribution for different refractive indices; the results showed good agreement with the results for simple analytic size distribution solutions.

The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data.

The comparison of the angular light-scattering method (ALSM) and the spectral extinction method (SEM) in solving the inverse problem of aerosol size distribution (ASD) are studied. The inverse problem is solved by a SPSO-DE hybrid algorithm, which is based on the stochastic particle swarm optimization (SPSO) algorithm and differential evolution (DE) algorithm. To improve the retrieval accuracy, the sensitivity analysis of measurement signals to characteristic parameters in ASDs is studied; and the corresponding optimal measurement angle selection region for ALSM and optimal measurement wavelength selection region for SEM are proposed, respectively. Results show that more satisfactory convergence properties can be obtained by using the SPSO-DE hybrid algorithm. Moreover, short measurement wavelengths and forward measurement angles are beneficial to obtaining more accurate results. Then, common monomodal and bimodal ASDs are estimated under different random measurement errors by using ALSM and SEM, respectively. Numerical tests show that retrieval results by using ALSM show better convergence accuracy and robustness than those by using SEM, which is attributed to the distribution of the objective function value. As a whole, considering the convergence properties and the independence on prior optical information, the ALSM combined with SPSO-DE hybrid algorithm provides a more effective and reliable technique to obtain the ASDs.

Aerosol particles are important due to their direct and indirect impacts on climate. Within the planetary boundary layer (BL), these particles have a relatively short lifetime due to their frequent removal process by wet deposition. When aerosols are transported into the free troposphere (FT), their atmospheric lifetime increases significantly, making them representative of large spatial areas. In this work, we use a combination of in situ measurements performed at the high altitude PUY (Puy de Dôme, 45°46′ N, 2°57′ E, 1465 m a.s.l) station, together with LIDAR profiles at Clermont-Ferrand for characterizing FT conditions, and further characterize the physical properties of aerosol in this poorly documented area of the atmosphere. First, a combination of four criteria was used to identify whether the PUY station lies within the FT or within the BL. Results show that the PUY station is located in BL with frequencies ranging from 50% during the winter, up to 97% during the summer. Then, the classification is applied to a year-long dataset (2015) of particle size distribution data to study the differences in particle physical characteristics (size distribution) and black carbon (BC) concentrations between the FT and the BL. Although BC, Aitken, and the accumulation mode particles concentrations were higher in the BL than in the FT in winter and autumn, they were measured to be higher in the FT compared to BL in spring. No significant difference between the BL and the FT concentrations was observed for the nucleation mode particles for all seasons, suggesting a continuous additional source of nucleation mode particles in the FT during winter and autumn. Coarse mode particle concentrations were found higher in the FT than in the BL for all seasons and especially during summer. This indicates an efficient long-range transport of large particles in the FT from distant sources (marine and desert) due to higher wind speeds in the FT compared to BL. For FT air masses, we used 204-h air mass back-trajectories combined with boundary layer height estimations from ECMWF ERA-Interim to assess the time they spent in the FT since their last contact with the BL and to evaluate the impact of this parameter on the aerosol properties. We observed that even after 75 h without any contact with the BL, FT aerosols preserve specific properties of their air mass type.

This work use observed and modeled data to trace a basic model that describes how the bulk chemical composition can be used to determine the aerosol size-dependency of hygroscopicity inside the urban aerosol pollution plume from Manaus, Brazil. The procedure is then used to predict the Cloud Condensation Nuclei (CCN) concentration (N C C N) from the Aerosol Size Distribution (ASD). The work briefly described hourly averaged data of ASD, Black Carbon size distribution (BCSD), Black Carbon mass concentration (BC), N C C N , and aerosol size hygroscopicity (κ) observed about 70 km downwind of the City of Manaus, inside the amazon rain forest, during 60 days of 2014, in the course of the rainy season. It uses a description of aerosol chemical composition obtained previously in the city of São Paulo, Brazil, as starting point to formulate a model that describes how particles in the pollution plume act as CCN as a function of their sizes and bulk chemical composition. A parameterization based on a polynomial fitting is proposed to determine BCSD from the BC. The measured and parameterized BCSD agree very well with more than 98% of the observed BCSDs, presenting a correlation coefficient larger than 0.9 with observation. The parameterized BC number concentration is also very well represented, with a correlation coefficient of 0.91 and a slope of 0.99 in comparison with observations. This work also studies how soot particles are incorporated in the CCN population and propose a parameterization to represent it. Simulations suggest that the larger BC particles are only partially incorporated as CCN and BC is a constraint to the fraction of aerosols that can act as CCN in all size ranges. The simulations also suggest that the incorporation of BC as CCN is probably only effective through coagulation in the presence of the wet phase. In addition, the work compares different strategies to predict observed N C C N from ASD. It is shown that the strategy presented can substantially improve the results of comparison of modeled and measured data from as bad as 2.14 ± 0.65 to as good as 1.02 ± 0.17. This study shows that the knowledge of the bulk chemical composition can be used to predict both the size-resolved chemical composition and mixing state, reducing the number of parameters needed to predict N C C N. • Model to define CCN activity from aerosol size distribution and chemical composition. • How soot particles are incorporated in the CCN population. • Parameterization of black carbon size distribution from black carbon mass concentration. • Comparison of different strategies to predict observed CCN concentration. [ABSTRACT FROM AUTHOR]

The aerosol particle size distributions of uranium and its daughter products were studied and determined in the area of the Rožná mine, which is the last active uranium mine in the Czech Republic. A total of 13 samples were collected using cascade impactors from three sites that had the highest expected levels of dust, namely, the forefield, the end of the ore chute and an area close to workers at the crushing plant. The characteristics of most size distributions were very similar; they were moderately bimodal, with a boundary approximately 0.5 μm between the modes. The activity median aerodynamic diameter (AMAD) and geometric standard deviation (GSD) were obtained from the distributions beyond 0.39 μm, whereas the sizes of particles below 0.39 μm were not differentiated. Most AMAD and GSD values in the samples ranged between 3.5 and 10.5 μm and between 2.8 and 5.0, respectively. The geometric means of the AMADs and GSDs from all of the underground sampling sites were 4.2 μm and 4.4, respectively, and the geometric means of the AMADs and GSDs for the crushing plant samplings were 9.8 μm and 3.3, respectively. The weighted arithmetic mean of the AMADs was 4.9 μm, with a standard error of 0.7 μm, according to the numbers of workers at the workplaces. The activity proportion of the radon progeny to 226 Ra in the aerosol was 0.61. [ABSTRACT FROM AUTHOR]

Size-resolved particulate matter (PM) samples were collected with a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI) at a sub-urban site (Tung Chung) in Hong Kong for four non-consecutive months representing four seasons from 2011 to 2012. Major chemical components were water-soluble anions (i.e., Cl − , NO 3 − , and SO 4 2 − ), cations (i.e., NH 4 + , Na + , K + , and Ca 2 + ), organic and elemental carbon and elements. Both chemical mass closure and positive matrix factorization (PMF) were employed to understand the chemical composition, resolve particle size modes, and evaluate the PM sources. Tri-modal size distributions were found for PM mass and major chemical components (e.g., SO 4 2 − , NH 4 + , and OC). Mass median aerodynamic diameters (MMADs) with similar standard deviations (1.32 < σ < 1.42) were 0.4, 0.7 and 3.8 μm, consistent with condensation, droplet and coarse modes. A bi-modal distribution peaking at condensation and droplet modes was found for EC, with a single mode peaking at 3.8 μm for Cl − . Besides secondary SO 4 2 − , carbonaceous aerosol dominated the condensation mode with 27% by engine exhaust and 18–19% each by residual oil combustion (shipping) and coal/biomass burning. Secondary SO 4 2 − is also the most dominant component in the droplet mode, accounting for 23% of PM mass, followed by an industrial source (19%). Engine exhaust, secondary NO 3 − , and sea salt each accounted for 13–15% of PM mass. Sea salt and soil are the dominated sources in the coarse mode, accounting for ~ 80% of coarse mass. [ABSTRACT FROM AUTHOR]

The size characteristics of atmospheric aerosol over the tropical region of Lagos, Southern Nigeria were investigated using two years of continuous spectral aerosol optical depth measurements via the AERONET station for four major bands i.e. blue, green, red and infrared. Lagos lies within the latitude of 6.465°N and longitude of 3.406°E. Few systems of dispersion model was derived upon specified conditions to solve challenges on aerosols size distribution within the Stokes regime. The dispersion model was adopted to derive an aerosol size distribution (ASD) model which is in perfect agreement with existing model. The parametric nature of the formulated ASD model shows the independence of each band to determine the ASD over an area. The turbulence flow of particulates over the area was analyzed using the unified number (Un). A comparative study via the aid of the Davis automatic weather station was carried out on the Reynolds number, Knudsen number and the Unified number. The Reynolds and Unified number were more accurate to describe the atmospheric fields of the location. The aerosols loading trend in January to March (JFM) and August to October (ASO) shows a yearly 15% retention of aerosols in the atmosphere. The effect of the yearly aerosol retention can be seen to partly influence the aerosol loadings between October and February. [ABSTRACT FROM AUTHOR]

As one part of a chemical-microphysical model, a stratospheric aerosol model has been developed for the implementation in the Hamburg climate model ECHAM. This model treats the formation, the development and the transport of stratospheric sulfuric acid aerosol. The aerosol size distribution and the chemical composition of the droplets are calculated dependent on the atmospheric conditions (temperature, air pressure) and the partial pressure of H2SO4 and H2O. Binary homogeneous nucleation of H2SO4/H2O condensation and evaporation of H2SO4 and H2O, Brownian coagulation and gravitational sedimentation are included. Sensitivity studies with the microphysical model were performed in order to study the influence of the nucleation and condensation parameterization on the aerosol size distribution. The impact of the initial conditions (temperature, water vapor, SO2, OH) on the aerosol size distribution is also investigated. Box simulations of the stratospheric background aerosol are in good agreement with in situ measurements above 73 hPa in middle and high latitudes. The model is able to reproduce important features of the stratospheric aerosol, like the observed strong increase of the aerosol size ratio above 50 hPa and the decrease of the aerosol mixing ratio. Due to the neglect of advection and diffusion processes the microphyiscal model alone is not able to reproduce observations from regions with strong vertical exchange processes. The simulated temporal development of the aerosol spectrum in a volcanically perturbed atmosphere is close to observations. After four to five years the background level is reached again.

To evaluate PM 2.5 contributions to light scattering under different air pollution levels, PM 2.5 and its major chemical components, PM 10 , size-segregated water-soluble ions, and aerosol scattering coefficient (b sp ) under dry conditions were measured at an urban site in Beijing in January 2013 when heavy pollution events frequently occurred. Measurements were categorized into three pollution levels including heavy-polluted (Air Quality Index (AQI) ≥ 200), light-polluted (200 > AQI ≥ 100) and clean periods (AQI < 100). The average PM 2.5 mass concentration was 248 μg m −3 during the heavy-polluted period, which was 2.4 and 5.6 times of those during the light-polluted (104 μg m −3 ) and clean (44 μg m −3 ) periods, respectively. The concentrations of SO 4 2− , NO 3 − and NH 4 + increased much more than those of OC and EC during the heavy-polluted period compared with those during the light-polluted and clean periods. Good correlations between PM 2.5 and b sp were found (R 2 > 0.95) during the different pollution levels. The mass scattering efficiency (MSE) of PM 2.5 was 4.9 m 2 g −1 during the heavy-polluted period, which was higher than those during the light-polluted (4.3 m 2 g −1 ) and clean periods (3.6 m 2 g −1 ). To further evaluate the impact of individual chemical components of PM 2.5 on light scattering, a multiple linear regression equation of measured b sp against the mass concentration of (NH 4 ) 2 SO 4 , NH 4 NO 3 , Organic Matter (OM), EC, Fine Soil (FS), Coarse Matter (CM) and Other chemical compounds were performed. (NH 4 ) 2 SO 4 , NH 4 NO 3 and OM were the dominant species contributing to b sp under both dry and ambient conditions. OM contributed more to b sp than the sum of (NH 4 ) 2 SO 4 and NH 4 NO 3 did under the dry condition during all the pollution periods and this was also the case under the ambient condition during the light-polluted and clean periods. However, the total contributions of (NH 4 ) 2 SO 4 and NH 4 NO 3 to b sp under the ambient condition was 55%, much more than the 29% contribution from OM during the heavy-polluted period. High (NH 4 ) 2 SO 4 and NH 4 NO 3 concentrations and their hygroscopicity were the main reasons causing visibility degradation during the heavy-polluted period, and the effect can be enhanced under high RH conditions. [ABSTRACT FROM AUTHOR]

Aerosol optical properties including aerosol optical depth (AOD), Ångström exponent ( α ), single scattering albedo (SSA), aerosol size distribution and refractive index at urban Wuhan in Central China are investigated based on the measurements from a CIMEL sun-photometer during 2007–2013. AOD 500 nm is found to be relatively high all year round and the highest value 1.52 occurs in June 2012 and the lowest (0.57) in November 2012. α shows a significant monthly variation, with the highest value in June 2010 (1.71) and the lowest value (0.78) in April 2012. Analysis of AOD and α frequencies indicate that this region is populated with fine-mode particles. Monthly variations of SSA for total, fine and coarse-mode particles are closely related to the aerosol hygroscopic growth, fossil fuel and biomass burning. The aerosol volume size distributions (bi-modal pattern) show distinct differences in particle radius for different seasons, the radius for fine-mode particles generally increase from spring to summer month, for example, the highest peak is around radius 0.15 μm in March, while the peak radius is around 0.25 μm in June. Finally, monthly statistics of real and imaginary parts of the complex refractive index are analyzed, the highest averages of real (1.50) and imaginary parts (0.0395) are found in spring and autumn, respectively at wavelength 440–1020 nm. [ABSTRACT FROM AUTHOR]

Volcanic plume aerosol following the paroxysmal event of Mount Etna (Italy) in February 21st - 26th, 2021 was detected in Naples area (Italy), together with transport of Saharan dust aerosol, combining lidar, sunphotometer and satellite observations with back-trajectories and dispersion models simulations. Lidar data allowed to clearly distinguish the two main aerosol components, to investigate the spectral dependence of the aerosol optical properties and to retrieve their microphysical properties, essential for a detailed aerosol characterization. A new Monte Carlo algorithm, capable of retrieving the particle size distribution from lidar measurements, was applied. Lidar results are in good agreement with columnar integrated sunphotometer data. This combination of novel lidar observations of the vertically-resolved aerosol microphysics, column observations and modelling allows for a more complete description of multi-layered aerosol conditions. [Display omitted] • Volcanic aerosol was observed by remote sensing instruments in Naples (Italy) after a lava fountain events of Mount Etna. • Aerosol optical and microphysical characterization allowed to discriminate volcanic aerosol from Saharan dust. • Aerosol size distributions were retrieved from lidar-derived optical properties averaged in the observed layers. [ABSTRACT FROM AUTHOR]

Asian residential communities are usually dotted with various spot pollution sources (SPS), such as restaurants, temples, and home factories, with traffic arteries passing through, resulting in higher intra-urban pollution variability compared with their western counterparts. Thus, it is important to characterize spatial variability of pollutant levels in order to assess accurately residents' exposures in their communities. The objectives of this study are to assess the actual pollutant levels and variability within an Asian urban area and to evaluate the influence of vehicle emission and various SPS on the exposure levels within communities. Real-time monitoring was conducted for a total of 123 locations for particulate matter (PM) and CO in Taipei metropolitan, Taiwan. The mean concentrations for PM1, PM2.5, PM10, and CO are 29.8 ± 22.7, 36.0 ± 25.5, 61.9 ± 35.0 μgm−3 and 4.0 ± 2.5 ppm, respectively. The mean values of PM1/PM2.5 and PM2.5/PM10 are 0.80 ± 0.10 and 0.57 ± 0.15, respectively. PM and CO levels at locations near SPS could be increased by 3.5–4.9 times compared with those at background locations. Regression results show that restaurants contribute significantly 6.18, 6.33, 7.27 μgm−3, and 1.64 ppm to community PM1, PM2.5, PM10, and CO levels, respectively; while the contribution from temples are 13.2, 15.1, and 17.2 μgm−3 for PM1, PM2.5 and PM10, respectively. Additionally, construction sites elevate nearby PM10 levels by 14.2 μgm−3. At bus stops and intersections, vehicle emissions increased PM1 and PM2.5 levels by 5 μgm−3. These results demonstrate significant contribution of community sources to air pollution, and thus the importance of assessing intra-community variability in Asian cities for air pollution and health studies. The methodology used is applicable to other Asian countries with similar features. [ABSTRACT FROM AUTHOR]

Abstract: In this study, two different methods for the measurement of the sulfuric acid aerosol which is formed in wet flue gas cleaning processes have been investigated. The condensation particle counter (UFCPC, PALAS GmbH) provides information about the number concentration. With the electrical low pressure impactor (ELPI+, Dekati Ltd.) also the size evaluation is possible. Both measurement methods reveal number concentrations above 108 cm−3 under well controlled conditions in a pilot plant and the good conformance of the both methods is shown. With the ELPI+ the effect of dilution on the size of the volatile aerosol can be observed. The predicted trend of an existing simulation tool can be verified: the higher the sulfuric acid concentration, the larger are the droplet sizes. The number concentration, however, doesn´t change considerably when altering the sulfuric acid concentration. [Copyright &y& Elsevier]

Abstract: Aerosol size distributions of observed mass concentrations at the Naiman site in Inner Mongolia that is one of the major Asian dust source regions have been examined for the period from April 2010 to July 2012. The total number of 262 sampled data using the 10-stage quartz crystal microbalance (QCM) cascade impactor is obtained by presetting the frequency changes of 40 Hz during April 2010, 60 Hz for the period of 28 April–16 September 2010 and 70 Hz from 1 November 2010–29 July 2012. The total mass concentrations (PM10) measured by the QCM cascade impactor are modified to have the same sampling time of 60 min with the help of the 1-h averaged PM10 concentration measured by the beta gauge at the same site. These modified QCM data are classified into the local dust emission case of 196 and the dust advection case of 66. The local dust emission case is defined when the calculated dust flux with the two-level (3 m and 15 m high) measured PM10 concentrations by the beta-gauge is upward and the PM10 concentration measured at 3 m high exceeds 100 μg m−3 while all the rest of QCM sampled data are classified as the dust advection case. The results indicate that the spectral mass concentration distribution of the local dust emission case shows a two-modal distribution with one additional mode of the large particle that cannot be resolved by the QCM cascade impactor whereas that of the advection case reveals a three-modal distribution with one additional unresolved large particle mode. The percent spectral mass concentration distribution of the unresolved mode (stage 1) for the local dust emission case is larger than that for the dust advection case. The modal distributions of both cases can be regressed optimally with log-normal distribution functions. The resolved log-normal distribution functions of the mass concentration distribution by the QCM cascade impactor are found to be the particle mean diameter (the standard deviation) of 0.28 (2.07) and 3.15 μm (1.41 μm) for the local emission case and 0.16 (1.51), 0.60 (1.41) and 2.88 μm (1.38 μm) for the advection case. This clearly suggests that the spectral mass concentration shifts toward the larger particle size for the local emission case. [Copyright &y& Elsevier]