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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]

Exploring the relative importance of different routes in SARS‐CoV‐2 transmission is crucial in infection prevention. However, even in the same environmental setting, the relative importance of different routes has varied in different studies. We hypothesize that respiratory aerosol size and number distribution might play a key role. In this study, size and number distribution of respiratory droplets emitted from breathing, talking, and coughing were identified from PubMed and Web of Science. The infection risk of SARS‐CoV‐2 via airborne, droplet, and fomite transmission routes was modeled in a household and a healthcare setting. The relative importance of three routes varied with different size distributions in both settings. Generally, the contribution of the airborne route increased with the volume percentage of respirable droplets emitted. And the increase of the total number of emitted droplets leads to an increase in the contribution of tdroplet route. In the healthcare setting, as the total number of emitted droplets increased from 110 to 4,973, the contribution of droplet route increased from 62.24% to 98.11%. Next, by considering the combination of breathing, coughing, and talking when the infected person was asymptomatic, the airborne route predominated over the droplet and contact routes. When the infected person had developed symptoms, that is, cough, the droplet route played a dominant role in SARS‐CoV‐2 transmission. In conclusion, risk analyses will be improved with improved sampling methods that enable characterization of viruses within respiratory droplets of different sizes. [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.

The Indo-Gangetic basin is one of the biggest, most populated and polluted regions in the world. Satellite- and ground-based data show strong seasonal variability of aerosol loading with a maximum during pre-monsoon (summer) season. In this study, decadal (2003–2012) variability of aerosol optical depth (AOD) derived from AERONET measurements over Kanpur is presented which indicates maximum AOD during 2003 and minimum during 2012. The aerosol size distribution (ASD) exhibits an increase in the radius and a decrease in the width of distribution. It shows an enhancement during 2003 and 2010 and diminished values during 2004, 2007, 2009 and 2011. The ASD is found to show a peak during summer season (pre-monsoon) throughout 2003–2012 only except the years 2008 and 2011. Moreover, for years 2008 and 2011 ASD showed a peak value during a monsoon month (July). Changes in the spectrum of ASD are explained in terms of surface temperature and precipitation. Seasonal variation of aerosol radiative forcing and its climatic impacts have also been discussed. [ABSTRACT FROM AUTHOR]

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.

We use 10 years of data from the Department of Energy (DoE) Atmospheric Radiation Measurements (ARM) United States Southern Great Plains (SGP) site with nearby regional pollen and fungal spore measurements to indirectly estimate the seasonal influence of these two primary biological aerosol particles (PBAP). We estimate possible primary emissions of larger PBAP and PBAP rupture events, which form submicron organic aerosol during precipitation or high relative humidity. High pollen counts at two urban stations near SGP occur during late winter/early spring (day of year (DOY) 50–120) and late summer (DOY 240–310). Around 4–19 days per year show possible pollen events (PPE) when near‐surface lidar observations of daily linear particle depolarization ratio >0.1 are coincident with high organic aerosol fraction. For PPE days with rainfall, aerosol size distribution observations show enhanced submicron particle concentrations consistent with pollen rupture events. For fungal spores, high fungal spore counts occur during late spring/early summer (DOY 110–195) and late summer/autumn (DOY 220–340). Based on size distribution observations, up to 7% of days have possible fungal spore rupture events (PFE) with higher aerosol number count specifically over the range expected for fungal spore fragment mobility diameter (20–50 nm). These short‐lived PFE correlate with rainfall or occur after prolonged exposure to rainfall (e.g., >10 h). While the SGP site lacks direct measurements of bioaerosol and large particle sizes, this analysis suggests that PBAP primary emissions and rupture events could occur about 32 days per year, representing an important component of the aerosol budget during seasonal emissions. Plain Language Summary: Primary biological aerosol particles (PBAP) are emitted directly from the Earth's surface and can include pollen, fungal spores, and bacteria. They can act as nuclei for water droplets or ice crystals and are known to impact clouds and precipitation, and may influence both the regional and the global climate and hydrological cycle. Because measurements of many PBAPs are sparse, we use a suite of atmospheric data from the ambient aerosol and meteorological measurements from the Department of Energy's Atmospheric Radiation Measurements at United States Southern Great Plains site to indirectly identify possible emissions of pollen and fungal spores from the land surface. We estimate that PBAP can contribute to the local aerosol burden, especially during their peak emission periods. Key Points: An average of 12 days per year are estimated as primary pollen event days with high interannual variabilityDuring primary pollen events with precipitation or high humidity, rupture events are indicated during ∼4 days per yearDuring or after the prolonged exposure of rainfall for >10 h, ∼20 days per year show evidence of fungal spore rupture events [ABSTRACT FROM AUTHOR]

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]

Exploring the relative importance of different routes in SARS-CoV-2 transmission is crucial in infection prevention. However, even in the same environmental setting, the relative importance of different routes has varied in different studies. We hypothesize that respiratory aerosol size and number distribution might play a key role. In this study, size and number distribution of respiratory droplets emitted from breathing, talking, and coughing were identified from PubMed and Web of Science. The infection risk of SARS-CoV-2 via airborne, droplet, and fomite transmission routes was modeled in a household and a healthcare setting. The relative importance of three routes varied with different size distributions in both settings. Generally, the contribution of the airborne route increased with the volume percentage of respirable droplets emitted. And the increase of the total number of emitted droplets leads to an increase in the contribution of tdroplet route. In the healthcare setting, as the total number of emitted droplets increased from 110 to 4,973, the contribution of droplet route increased from 62.24% to 98.11%. Next, by considering the combination of breathing, coughing, and talking when the infected person was asymptomatic, the airborne route predominated over the droplet and contact routes. When the infected person had developed symptoms, that is, cough, the droplet route played a dominant role in SARS-CoV-2 transmission. In conclusion, risk analyses will be improved with improved sampling methods that enable characterization of viruses within respiratory droplets of different sizes., (© 2023 Society for Risk Analysis.)

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

Transboundary haze from biomass burning is one of the most important air pollutions in Southeast Asia. The most recent serious haze episode occurred in 2015. Southern Thailand was affected by the haze during September to October when the particulate matter concentration hit a record high. We investigated physical and chemical characteristics of aerosols, including concentration and aerosol size distribution down to sub-micron sizes during haze episodes in 2013 and 2015 and, for reference, an insignificant haze period in 2017. The highest total suspended particulates and PM 10 levels in Hat Yai city were 340.1 and 322.5 µg/m3. The mass fractions were nanoparticles (< 100 nm) 3.1%-14.8% and fine particles (< 1 µm) 54.6%-59.1%. Polycyclic aromatic hydrocarbon size distributions in haze periods peaked at 0.75 µm and the concentrations are 2-30 times higher than the normal period. High molecular weight (4-6 ring) PAHs during the haze episode contribute to about 56.7%-88.0% for nanoparticles. The average values of benzo(a)pyrene toxic equivalency quotient were 3.34±2.54ng/m3 in the 2015 haze period but only 0.89±0.17 ng/m3 in 2017. It is clear that particles smaller than 1 µm, were highly toxic. Nanoparticles contributed 19.4%-26.0% of total BaP-TEQ , whereas the mass fraction is 13.1%-14.8%. Thus the nanoparticles were more carcinogenic and can cause greater health effect than larger particles. The fraction of BaP-TEQ for nanoparticles during 2017 non-haze period was nearly the same, while the mass fraction was lower. This indicates that nanoparticles are the significant source of carcinogenic aerosols both during haze and non-haze periods. Image, graphical abstract [ABSTRACT FROM AUTHOR]

In this study, black carbon (BC), particulate matter (PM), nitrogen oxides (NOx), and sulphur dioxide (SO2) were monitored between May 2019 and February 2020. During this sampling period, size-segregated particle samples were collected by a high-volume cascade impactor, once a week. Elemental carbon (EC) and organic carbon (OC) were investigated on the size-segregated particles. The study was carried out at Esenler district of Istanbul. Main sources in the vicinity of the sampling area are Central Coach Station of Istanbul, residential buildings, small-scale industrial facilities, and O-1 and O-2 highway connection. The average BC concentration was 2763 ± 1974 ng/m3. PM10 and PM2.5 concentrations were 38.2 ± 17.4 and 21.5 ± 12.4 μg/m3, respectively. BC comprised 12.8% and 7.2% of PM2.5 and PM10, respectively. Diurnal variation of BC had a similar trend with NO2 concentrations, which showed peak concentrations during rush hours. BC had high Pearson correlation coefficients with NO, NO2, and PM2.5. The geographical position of possible emission sources was estimated through conditional probability function. The Central Coach Station of Istanbul had the highest geographical possibility for BC sources. EC and OC exhibited bimodal size distribution. The coarse mode peak was at 0.95–1.5-μm size bin for OC, whilst it was at 1.5–3-μm size bin for EC. Since EC and BC exhibit the same origin with different measurement principles, we concluded that resuspension of road dust also contributed ambient BC concentrations. [ABSTRACT FROM AUTHOR]

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]

For understanding the aerosol characteristics over the Yellow Sea according to the air flow patterns in East Asia, the aerosol volume concentration distribution by particle size (size distribution) of the shipborne samples collected in the KORUS-AQ campaign is examined in conjunction with air quality (AQ) model simulations and air parcel trajectory analyses. Cluster analyses of the air parcel trajectories show that 42% of the collected air samples originated in Korea and Japan, 30% in inland/east-coast China, 16% in the highlands of Inner Mongolia, and 11% in the East China Sea. The aerosol size distribution varies characteristically according to the upstream path of individual trajectory clusters; particles of diameters <1 μm dominate when the upstream pathways include China, Korea, and/or Japan, that are significant sources of anthropogenic aerosols. Air flows from the East China Sea, a region virtually free of anthropogenic aerosol sources, show aerosol concentrations peaks at larger sizes of 1–5 μm. The flows from the Inner Mongolia are characterized by a bimodal distribution with a peak at 0.7 μm and another peak of a similar magnitude at diameters >2 μm, indicating a mixed industrial-dust aerosol type in which the dust particles from the Inner Mongolia is mixed with fine particles in the industrialized northeast China. Model studies for cases of typical air flow trajectory groups show that the model simulates the spatial distribution of the satellite-observed particulate matter reasonably, but underestimates the observed volume concentration of fine particles <1 μm. [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]

Presently, both in rural areas and in cities open fireplaces are still present and large quantities of wood are combusted every year. The present study aims to characterize aerosol size distribution, chemical composition and deposition in the human respiratory tract of particles emitted during the combustion of logs of oak in an open fireplace installed in the living room of a typical village house. CO 2 and CO levels and aerosol size distribution have been continuously monitored and a PM 10 sampler with two types of filters for chemical and microscopic analysis was also installed. The increment, between the operating periods and the indoor background, in the organic carbon and PM 10 concentration due to the use of the fireplace is 15.7 ± 0.6 (mean ± standard deviation) and 58.5 ± 6.2 μg m −3 , respectively. The two main polluting processes during the operation of the fireplace are the ignition with the subsequent refueling and the final cleaning of the residual ashes. In both phases mean values around 1800 particles cm −3 with CMD of 0.15 μm were measured. However, while PM 10 levels of 130 ± 120 μg m −3 were estimated for the ignition stage, values of 200 ± 200 μg m −3 were obtained during the final cleaning step. Assessment conducted according to ISO standard 7708:1995, demonstrated that a person who stays in a living room when an open fireplace is lit will inhale, on average, 217 μg m −3 and 283 μg m −3 during the ignition and the refueling stages, respectively. Subsequent refueling proved to be much less polluting. The ashes removal can also be very polluting and dangerous to health if there are hidden small incandescent embers among the ashes (estimated PM 10 of 132 μg m −3 ), reaching a CO 2 level of 1940 ppm and a dangerous level of CO of 132 ppm. [ABSTRACT FROM AUTHOR]

An eye-safe 1 . 5 μ m visibility lidar is presented in this work considering in situ particle size distribution, which can be deployed in crowded places like airports. In such a case, the measured extinction coefficient at 1 . 5 μ m should be converted to that at 0 . 55 μ m for visibility retrieval. Although several models have been established since 1962, the accurate wavelength conversion remains a challenge. An adaptive inversion algorithm for 1 . 5 μ m visibility lidar is proposed and demonstrated by using the in situ Angstrom wavelength exponent, which is derived from an aerosol spectrometer. The impact of the particle size distribution of atmospheric aerosols and the Rayleigh backscattering of atmospheric molecules are taken into account. Using the 1 . 5 μ m visibility lidar, the visibility with a temporal resolution of 5 min is detected over 48 h in Hefei ( 31 . 83 ∘ N , 117 . 25 ∘ E ). The average visibility error between the new method and a visibility sensor (Vaisala, PWD52) is 5.2% with the R-square value of 0.96, while the relative error between another reference visibility lidar at 532 nm and the visibility sensor is 6.7% with the R-square value of 0.91. All results agree with each other well, demonstrating the accuracy and stability of the algorithm. [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]