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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

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