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We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44′ N, 27°33′ E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90 % of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25 % or 14 %) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3 % and 36 ± 5 % for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17 % and 30 % were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization.

An aethalometer was employed in a 1-year campaign (November 2014–November 2015) in Nanjing, China, that aimed to estimate the contributions of black carbon (BC; annual average ± std = 4.0 ± 3.3 µg m–3) and non-BC absorbers, such as brown carbon, to the aerosol absorption coefficient. We applied two methods: 1) the traditional calculation from the aethalometer data, assuming an absorption Angstrom exponent (AAE) of unity for BC (“AE method”), which provided an overall average of 27.2% for the non-BC contribution, and 2) a recently developed method based on the wavelength dependence of AAE (the “WDA method”), which indicated the existence of non-BC absorbers in 25.3% of the samples on average. We utilized trajectory and source area analyses and, in agreement with the results from other studies in this region, verified biomass burning emission sources, mainly to the northwest of the measurement site.

The relationship between aerosol hygroscopicity and cloud droplet activation was studied at the Puijo measurement station in Kuopio, Finland, during the autumn 2014. The hygroscopic growth of 80, 120 and 150 nm particles was measured at 90 % relative humidity with a hygroscopic tandem differential mobility analyzer. Typically, the growth factor (GF) distributions appeared bimodal with clearly distinguishable peaks around 1.0–1.1 and 1.4–1.6. However, the relative contribution of the two modes appeared highly variable reflecting the probable presence of fresh anthropogenic particle emissions. The hygroscopicity-dependent activation properties were estimated in a case study comprising four separate cloud events with varying characteristics. At 120 and 150 nm, the activation efficiencies within the low- and high-GF modes varied between 0–34 and 57–83 %, respectively, indicating that the less hygroscopic particles remained mostly non-activated, whereas the more hygroscopic mode was predominantly scavenged into cloud droplets. By modifying the measured GF distributions, it was estimated how the cloud droplet concentrations would change if all the particles belonged to the more hygroscopic group. According to κ-Köhler simulations, the cloud droplet concentrations increased up to 70 % when the possible feedback effects on effective peak supersaturation (between 0.16 and 0.29 %) were assumed negligible. This is an indirect but clear illustration of the sensitivity of cloud formation to aerosol chemical composition., published version, peerReviewed

Ambient inhalable particulate matter (PM) is a serious health concern worldwide, but especially so in China where high PM concentrations affect huge populations. Atmospheric processes and emission sources cause spatial and temporal variations in PM concentration and chemical composition, but their influence on the toxicological characteristics of PM are still inadequately understood. In this study, we report an extensive chemical and toxicological characterization of size-segregated urban air inhalable PM collected in August and October 2013 from Nanjing, and assess the effects of atmospheric processes and likely emission sources. A549 human alveolar epithelial cells were exposed to day- and nighttime PM samples (25, 75, 150, 200, 300 μg/ml) followed by analyses of cytotoxicity, genotoxicity, cell cycle, and inflammatory response. PM10–2.5 and PM0.2 caused the greatest toxicological responses for different endpoints, illustrating that particles with differing size and chemical composition activate distinct toxicological pathways in A549 cells. PM10–2.5 displayed the greatest oxidative stress and genotoxic responses; both were higher for the August samples compared with October. In contrast, PM0.2 and PM2.5–1.0 samples displayed high cytotoxicity and substantially disrupted cell cycle; August samples were more cytotoxic whereas October samples displayed higher cell cycle disruption. Several components associated with combustion, traffic, and industrial emissions displayed strong correlations with these toxicological responses. The lower responses for PM1.0–0.2 compared to PM0.2 and PM2.5–1.0 indicate diminished toxicological effects likely due to aerosol aging and lower proportion of fresh emission particles rich in highly reactive chemical components in the PM1.0–0.2 fraction. Different emission sources and atmospheric processes caused variations in the chemical composition and toxicological responses between PM fractions, sampling campaigns, and day and night. The results indicate different toxicological pathways for coarse-mode particles compared to the smaller particle fractions with typically higher content of combustion-derived components. The variable responses inside PM fractions demonstrate that differences in chemical composition influence the induced toxicological responses. &nbsp

Urban air particulate pollution is a known cause for adverse human health effects worldwide. China has encountered air quality problems in recent years due to rapid industrialization. Toxicological effects induced by particulate air pollution vary with particle sizes and season. However, it is not known how distinctively different photochemical activity and different emission sources during the day and the night affect the chemical composition of the PM size ranges and subsequently how it is reflected to the toxicological properties of the PM exposures. The particulate matter (PM) samples were collected in four different size ranges (PM10-2.5; PM2.5-1; PM1-0.2 and PM0.2) with a high volume cascade impactor. The PM samples were extracted with methanol, dried and thereafter used in the chemical and toxicological analyses. RAW264.7 macrophages were exposed to the particulate samples in four different doses for 24 h. Cytotoxicity, inflammatory parameters, cell cycle and genotoxicity were measured after exposure of the cells to particulate samples. Particles were characterized for their chemical composition, including ions, element and PAH compounds, and transmission electron microscopy (TEM) was used to take images of the PM samples. Chemical composition and the induced toxicological responses of the size segregated PM samples showed considerable size dependent differences as well as day to night variation. The PM10-2.5 and the PM0.2 samples had the highest inflammatory potency among the size ranges. Instead, almost all the PM samples were equally cytotoxic and only minor differences were seen in genotoxicity and cell cycle effects. Overall, the PM0.2 samples had the highest toxic potential among the different size ranges in many parameters. PAH compounds in the samples and were generally more abundant during the night than the day, indicating possible photo-oxidation of the PAH compounds due to solar radiation. This was reflected to different toxicity in the PM samples. Some of the day to night difference may have been caused also by differing wind directions transporting air masses from different emission sources during the day and the night. The present findings indicate the important role of the local particle sources and atmospheric processes on the health related toxicological properties of the PM. The varying toxicological responses evoked by the PM samples showed the importance of examining various particle sizes. Especially the detected considerable toxicological activity by PM0.2 size range suggests they're attributable to combustion sources, new particle formation and atmospheric processes.

Long-term in situ measurements of aerosol–cloud interactions are usually performed in measurement stations residing on hills, mountains, or high towers. In such conditions, the surface topography of the surrounding area can affect the measured cloud droplet distributions by increasing turbulence or causing orographic flows and thus the observations might not be representative for a larger scale. The objective of this work is to analyse, how the local topography affects the observations at Puijo measurement station, which is located in the 75 m high Puijo tower, which itself stands on a 150 m high hill. The analysis of the measurement data shows that the observed cloud droplet number concentration mainly depends on the cloud condensation nuclei (CCN) concentration. However, when the wind direction aligns with the direction of the steepest slope of the hill, a clear topography effect is observed. This finding was further analysed by simulating 3-D flow fields around the station and by performing trajectory ensemble modelling of aerosol- and wind-dependent cloud droplet formation. The results showed that in typical conditions, with geostrophic winds of about 10 m s−1, the hill can cause updrafts of up to 1 m s−1 in the air parcels arriving at the station. This is enough to produce in-cloud supersaturations (SSs) higher than typically found at the cloud base of ∼ 0.2 %), and thus additional cloud droplets may form inside the cloud. In the observations, this is seen in the form of a bimodal cloud droplet size distribution. The effect is strongest with high winds across the steepest slope of the hill and with low liquid water contents, and its relative importance quickly decreases as these conditions are relaxed. We therefore conclude that, after careful screening for wind speed and liquid water content, the observations at Puijo measurement station can be considered representative for clouds in a boreal environment., published version, peerReviewed

The relationship between aerosol hygroscopicity and cloud droplet activation was studied at the Puijo measurement station in Kuopio, Finland, during the autumn 2014. The hygroscopic growth of 80, 120 and 150 nm particles was measured at 90 % relative humidity with a hygroscopic tandem differential mobility analyzer. Typically, the growth factor (GF) distributions appeared bimodal with clearly distinguishable peaks around 1.0‒1.1 and 1.4‒1.6. However, the relative contribution of the two modes appeared highly variable reflecting the varying presence of fresh anthropogenic particle emissions. The hygroscopicity-dependent activation properties were estimated in a case study comprising three separate cloud events with varying characteristics. At 120 and 150 nm, the activation efficiencies within the low- and high-GF modes varied between 0‒0.33 and 0.66‒0.86, respectively, indicating that the less hygroscopic particles remained almost non-activated, whereas the more hygroscopic mode was predominantly scavenged into cloud droplets. By modifying the measured GF distributions, it was estimated how the cloud droplet concentrations would change if all the particles belonged to the more hygroscopic group. According to the κ-Köhler simulations, the cloud droplet concentrations increased up to 70 % with increasing hygroscopicity. This is an indirect but clear illustration of the sensitivity of cloud formation to aerosol chemical composition.