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Pollen has important implications for health, but also for the climate as it can act as cloud condensation nuclei or ice nuclei in cloud processing. Active remote sensing instruments equipped with polarization capability can extend the detection of pollen from the surface up to several kilometres in the atmosphere maintaining continuous and high time resolution operation. In this study, we use a synergy of three lidars, namely, a multi-wavelength PollyXT lidar, a Vaisala CL61 ceilometer and a Halo Photonics StreamLine Doppler lidar, to investigate the optical properties of birch pollen particles. All three lidars are equipped with polarization channels enabling the investigation of the wavelength dependence at 355, 532, 910 and 1565 nm. Together with pollen observations from a Hirst-type spore sampler and aerosol in situ observations, we were able to characterize the linear particle depolarization ratio (PDR) and backscatter-related Angstrom exponents of the pollen particles. Both optical properties have been extensively used in aerosol classification algorithms and they are therefore highly desired in the lidar community. We found that birch pollen exhibits a spectral dependence in the PDR, and its classification is feasible when, preferably, two or more polarization wavelengths are available.

Ice nucleating particles (INPs) are particles in the atmosphere that are able to initiate the freezing of water droplets, a process known as ice nucleation. INPs are important to study because they play a crucial role in many atmospheric processes, including the formation of clouds, precipitation, and the radiative properties of clouds. For example, INPs can influence the concentration, size, and shape of ice crystals in clouds, which can in turn affect the reflectivity and lifetime of the clouds. This can have significant impacts on Earth's radiative balance and climate. The most relevant process of ice crystal formation in mixed-phase clouds (MPC) is by immersion freezing (Ansmann et al., 2009). Immersion freezing takes place when an INP is immersed in a water droplet and freezing is triggered on the particle's surface. In this research, we present a series of INP concentration measurements obtained using a novel assay under development at the Finnish Meteorological Institute in Helsinki. The focus of our research is to evaluate the consistency and replicability of these measurements. To determine the contribution of different aerosols to the INP spectrum at different temperatures, we collect atmospheric particles onto membrane filters and analyze the concentration of INPs in a laboratory freezing experiment. In this experiment, we produce an aqueous solution with collected atmospheric particles and monitor identical aliquots of the aqueous solution while they are cooled until freezing. Finally, using the frozen fraction of aliquots at a given temperature, the volume of each aliquot, and the sample's air volume, the cumulative number of INPs in the given sample at each temperature is calculated following (Vali, 2019). Three automatic samplers were run in parallel to collect particles onto the membrane filters using different sampling schemes. For example, collecting daily samples with three different sampling flows. With these measurements, we will analyze the influence of the sampled air volume, air flow, and sampling duration on the INP concentration measurements. ReferencesAnsmann, A. et al. (2009) Evolution of the ice phase in tropical altocumulus: SAMUM lidar observations over Cape Verde Atmosphere, 9(9), 357Vali, G., (2019). Revisiting the differential freezing nucleus spectra derived from drop-freezing experiments: Methods of calculation, applications, and confidence limits. Atmos. Meas. Tech., 12(2), 1219-1231. https://doi.org/10.5194/amt-12-1219-2019

Active remote sensors equipped with the capability to detect polarization, a shape relevant parameter, are essential to aerosol particle identification in the vertical domain. Most commonly, the linear particle depolarization ratio has been available at the shorter wavelengths of 355 nm and/or 532 nm. Recently, linear particle depolarization ratios at longer wavelengths (910 nm, 1064 nm and, 1565 nm) have emerged to the lidar aerosol research. In this study, a synergy of three lidars, namely a PollyXT lidar, a Vaisala CL61 ceilometer and a Halo Photonics StreamLine Pro Doppler lidar, and in situ aerosol and pollen observations have been utilized to investigate the spectral dependence of birch and pine pollen particles. We found that regardless of the pollen type, the linear particle depolarization ratio was subject to the amount of pollen and its relative contribution to the aerosol mixture in the air. More specifically, during the birch pollination characteristic linear particle depolarization ratios of 5 ± 2 % (355 nm), 28 ± 6 % (532 nm), 23 ± 6 % (910 nm) and, 33 ± 4 % (1565 nm) were retrieved at the pollen layer. Regarding the pine dominant period, the characteristic linear particle depolarization ratio of 6 ± 2 %, 43 ± 11 %, 22 ± 6 % and, 26 ± 3 %, was determined at 355 nm, 532 nm, 910 nm and, 1565 nm wavelengths, respectively. For birch, the linear particle depolarization ratio at 1565 nm was the highest followed by 532 nm and 910 nm wavelengths, respectively. A sharp decrease at 355 nm was evident for birch pollen. For pine pollen, a maximum at 532 nm wavelength was observed. There was no significant change in the linear particle depolarization ratio at 910 nm for the pollen types considered in this study. Given the low concentration of pollen in the air, the inclusion of the longer wavelengths (910 nm and 1565 nm) for the detection of birch and pine can be beneficial due to their sensitivity to trace large aerosol particles.

Small-scale wood combustion is a significant source of particulate emissions. Atmospheric transformation of wood combustion emissions is a complex process involving multiple compounds interacting simultaneously. Thus, an advanced methodology is needed to study the process in order to gain a deeper understanding of the emissions. In this study, we are introducing a methodology for simplifying this complex process by detecting dependencies of observed compounds based on a measured dataset. A statistical model was fitted to describe the evolution of combustion emissions with a system of differential equations derived from the measured data. The performance of the model was evaluated using simulated and measured data showing the transformation process of small-scale wood combustion emissions. The model was able to reproduce the temporal evolution of the variables in reasonable agreement with both simulated and measured data. However, as measured emission data are complex due to multiple simultaneous interacting processes, it was not possible to conclude if all detected relationships between the variables were causal or if the variables were merely co-variant. This study provides a step toward a comprehensive, but simple, model describing the evolution of the total emissions during atmospheric aging in both gas and particle phases. peerReviewed

A quantitative comparison study for Raman lidar and ceilometer observations, and for model simulations of mass concentration estimates of smoke particles is presented. Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios (PDRs) of this plume were measured to be 0.08±0.02 at 355 nm and 0.05±0.01 at 532 nm, suggesting the presence of partly coated soot particles or particles that have mixed with a small amount of dust or other non-spherical aerosol type. The layer-mean PDR at 355 nm (532 nm) decreased during the day from ∼ 0.11 (0.06) in the morning to ∼ 0.05 (0.04) in the evening; this decrease with time could be linked to the particle aging and related changes in the smoke particle shape properties. Lidar ratios were derived as 47±5 sr at 355 nm and 71±5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 ceilometer is presented from a sensor-provided attenuated backscatter coefficient to particle mass concentration (including the water vapor correction for high latitude for the first time). Aerosol backscatter coefficients (BSCs) were measured at four wavelengths (355, 532, 1064 nm from PollyXT and 910 nm from CL51). Two methods, based on a combined lidar and sun-photometer approach, are applied for mass concentration estimations from both PollyXT and the ceilometer CL51 observations. In the first method, no. 1, we used converted BSCs at 532 nm (from measured BSCs) by corresponding measured backscatter-related Ångström exponents, whereas in the second method, no. 2, we used measured BSCs at each wavelength independently. A difference of ∼ 12 % or ∼ 36 % was found between PollyXT and CL51 estimated mass concentrations using method no. 1 or no. 2, showing the potential of mass concentration estimates from a ceilometer. Ceilometer estimations have an uncertainty of ∼ 50 % in the mass retrieval, but the potential of the data lies in the great spatial coverage of these instruments. The mass retrievals were compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust (as indicated by MERRA-2 data) in the retrieved mass concentration is negligible considering the uncertainties, which also shows that ceilometer observations for mass retrievals can be used even without exact knowledge of the composition of the smoke-dominated aerosol plume in the troposphere.

The sources, sizes, components, and toxicological responses of particulate matter (PM) have demonstrated remarkable spatiotemporal variability. However, associations between components, sources, and toxicological effects in different-sized PM remain unclear. The purposes of this study were to 1) determine the sources of PM chemical components, 2) investigate the associations between components and toxicology of PM from Guangzhou high air pollution season. We collected size-segregated PM samples (PM

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

We carried out a closure study of aerosol-cloud interactions during stratocumulus formation using a large eddy simulation model UCLALES-SALSA and in situ observations from the 2020 sampling campaign at the Puijo SMEAR IV station in Kuopio, Finland. UCLALES-SALSA uses spectral bin microphysics for aerosols and hydrometeors and incorporates a full description of their interactions into the turbulent-convective radiation-dynamical model of stratocumulus. Typical closure studies use observations to assess agreement between aerosol properties and cloud droplet number concentration (CDNC) in updrafts. Here, the unique observational setup allowed a closer look into the aerosol size-composition dependence of droplet activation and droplet growth in turbulent boundary layer driven by surface forcing and radiative cooling. The model successfully described probability distribution of updraft velocities and aerosol activation efficiency curves, and nicely recreated the size distributions shapes for aerosol and cloud droplets. This is the first time such a detailed closure is achieved not only accounting for activation of cloud droplets in different updrafts, but also accounting for processes evaporating droplets and drizzle production through coagulation-coalescence. We studied two cases of cloud formation, one diurnal (24/09/2020) and one nocturnal (31/10/2020), with high and low aerosol loadings, respectively. Aerosol number concentrations differ more than an order of magnitude between cases and therefore, lead to CDNC of less than 100 cm-3 up to 1000 cm-3. Different aerosol loadings affected the supersaturation at the cloud base, and thus the minimum size of aerosol particles producing cloud droplets. Also, as the mean size of cloud droplets in the diurnal-high aerosol case was lower, the droplet evaporation process was found to be decreasing the observed CDNC more than in the low aerosol case. In addition, in the low aerosol case, the presence of large aerosol particles played a significant role on the droplet spectrum evolution as it promoted the drizzle formation through coalescence and collision processes enhanced by cyclic turbulence fluctuations. Also, during the event, the ice particle formation was observed due to subzero temperature at the cloud top. The studied cases are presented in detail and can be further used by the cloud modellers to test and validate their models in a well characterized modelling setup. We also provide recommendations on how increasing amount of information on aerosol properties could improve the understanding of processes affecting cloud droplet number and liquid water content in stratified clouds.

Despite a large number of studies, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in different sizes in total of for 21 measurement sites in Europe and Arctic. For 13 of those, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in-situ observations from Europe and five earth system models (ESM). We found that the trends of particle number concentrations were mostly consistent and decreasing in both, measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, were typically stronger in northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories. For EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, for others, the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showing clear differences in concentrations between remote and urban sites. To conclude, although anthropogenic mass emissions are harmonized in models, trends in different sized particles vary among the model due to assumptions in emission sizes and differences in how models treat size dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions.

The sources and chemical components of urban air particles exhibit seasonal variations that may affect their hazardousness to human health. Our aims were to investigate winter and spring variation in particulate matter (PM) sources, components and toxicological responses of different PM size fractions from samples collected in Guangzhou, China. Four size-segregated PM samples (PM

Upon a new measurement technique, it is possible to sharpen the determination of microphysical properties of cloud droplets using high resolving power imaging. The shape, size, and position of each particle inside a well-defined, three-dimensional sample volume can be measured with holographic methods without assumptions of particle properties. In-situ cloud measurements were carried out at the Puijo station in Kuopio, Finland, focusing on intercomparisons between cloud droplet analysers over the two months on September–November 2020. The novel holographic imaging instrument (ICEMET) was adapted to measure microphysical properties of liquid clouds and these values were compared to parallel measurements of cloud droplet spectrometer (FM-120) and particle measurements using a twin-inlet system. When the intercomparison was carried out during isoaxial sampling, our results showed good agreement in terms of variability between the instruments with the averaged ratios between ICEMET and FM-120 were 0.6 ± 0.2, 1.0 ± 0.5, and 1.2 ± 0.2 for total number concentration (Nd) of droplets, liquid water content (LWC), and median volume diameter (MVD), respectively. This agreement during isoaxial sampling was also confirmed by mutual information and Pearson correlation coefficients. The ICEMET observed liquid water content (LWC) was more reliably than FM-120 (without swivel-head mount), which was verified by comparing the estimated LWC to measured values whereas the twin-inlet DMPS system and FM-120 observations of Nd showed good agreement both in variability and amplitude. Field data revealed that ICEMET can detect small cloud droplets down to 5 μm via geometrical magnification.

We carried out a closure study of aerosol–cloud interactions during stratocumulus formation using a large eddy simulation model UCLALES–SALSA (University of California Los Angeles large eddy simulation model–sectional aerosol module for large applications) and observations from the 2020 cloud sampling campaign at Puijo SMEAR IV (Station for Measuring Ecosystem–Atmosphere Relations) in Kuopio, Finland. The unique observational setup combining in situ and cloud remote sensing measurements allowed a closer look into the aerosol size–composition dependence of droplet activation and droplet growth in turbulent boundary layer driven by surface forcing and radiative cooling. UCLALES–SALSA uses spectral bin microphysics for aerosols and hydrometeors, and incorporates a full description of their interactions into the turbulent-convective radiation-dynamical model of stratocumulus. Based on our results, the model successfully described the probability distribution of updraught velocities and consequently the size dependency of aerosol activation into cloud droplets, and further recreated the size distributions for both interstitial aerosol and cloud droplets. This is the first time such a detailed closure is achieved not only accounting for activation of cloud droplets in different updraughts, but also accounting for processes evaporating droplets and drizzle production through coagulation–coalescence. We studied two cases of cloud formation, one diurnal (24 September 2020) and one nocturnal (31 October 2020), with high and low aerosol loadings, respectively. Aerosol number concentrations differ more than 1 order of magnitude between cases and therefore, lead to cloud droplet number concentration (CDNC) values which range from less than 100 cm−3 up to 1000 cm−3. Different aerosol loadings affected supersaturation at the cloud base, and thus the size of aerosol particles activating to cloud droplets. Due to higher CDNC, the mean size of cloud droplets in the diurnal high aerosol case was lower. Thus, droplet evaporation in downdraughts affected more the observed CDNC at Puijo altitude compared to the low aerosol case. In addition, in the low aerosol case, the presence of large aerosol particles in the accumulation mode played a significant role in the droplet spectrum evolution as it promoted the drizzle formation through collision and coalescence processes. Also, during the event, the formation of ice particles was observed due to subzero temperature at the cloud top. Although the modelled number concentration of ice hydrometeors was too low to be directly measured, the retrieval of hydrometeor sedimentation velocities with cloud radar allowed us to assess the realism of modelled ice particles. The studied cases are presented in detail and can be further used by the cloud modellers to test and validate their models in a well-characterized modelling setup. We also provide recommendations on how increasing amount of information on aerosol properties could improve the understanding of processes affecting cloud droplet number and liquid water content in stratiform clouds.

Industrial processes, coal combustion, biomass burning (BB), and vehicular transport are important sources of atmospheric fine particles (PM2.5) and contribute to ambient air concentrations of health-hazardous species, such as heavy metals, polycyclic aromatic hydrocarbons (PAH), and oxygenated-PAHs (OPAH). In China, emission controls have been implemented to improve air quality during large events, like the Youth Olympic Games (YOG) in August 2014 in Nanjing. In this work, six measurement campaigns between January 2014 and August 2015 were undertaken in Nanjing to determine the effects of emission controls and meteorological factors on PM2.5 concentration and composition. PAHs, OPAHs, hopanes, n-alkanes, heavy metals, and several other inorganic elements were measured. PM2.5 and potassium concentrations were the highest in May-June 2014 indicating the prevalence of BB plumes in Nanjing. Emission controls substantially reduced concentrations of PM2.5 (31%), total PAHs (59%), OPAHs (37%), and most heavy metals (44-89%) during the YOG compared to August 2015. In addition, regional atmospheric transport and meteorological parameters partly explained the observed differences between the campaigns. The most abundant PAHs and OPAHs were benzo [b,k] fluoranthenes, fluoranthene, pyrene, chrysene, 1,8-naphthalic anhydride, and 9,10-anthracenedione in all campaigns. Carbon preference index and the contribution of wax n-alkanes indicated mainly biogenic sources of n-alkanes in May-June 2014 and anthropogenic sources in the other campaigns. Hopane indexes pointed to vehicular transport as the major source of hopanes, but contribution of coal combustion was detected in winter 2015. The results provide evidence to the local government of the impacts of the air protection regulations. However, differences between individual components were observed, e.g., concentrations of potentially more harmful OPAHs decreased less than concentrations of PAHs. The results suggest that the proportions of hazardous components in the PM2.5 may also change considerably due to emission control measures.

Little evidence is available regarding the impact of different sizes of inhaled particulate matter (PM) on inflammatory responses in healthy young adults in connection with toxicological responses. We conducted a five-time repeated measurement panel study on 88 healthy young college students in Guangzhou, China from December 2017 to January 2018. Blood samples were collected from each participant and tested for tumor necrosis factor alpha (TNF-α) levels every week for 5 consecutive weeks. Mass concentrations of ambient PM

Layers of biomass burning aerosol particles were observed in the lower troposphere, at 2 to 5 km height on 4 to 6 June 2019, over Kuopio, Finland. These long-range-transported smoke particles originated from a Canadian wildfire event. The most pronounced smoke plume detected on 5 June was intensively investigated. Optical properties were retrieved from the multi-wavelength Raman polarization lidar PollyXT. Particle linear depolarization ratios of this plume were measured to be 0.08 ± 0.02 at 355 nm and 0.05 ± 0.01 at 532 nm which were slightly higher than the values given in the literature. Non-spherical shaped aged smoke particles and/or the mixing with a small amount of fine dust particles could cause the observed increase in the particle linear depolarization ratios. Lidar ratios were derived as 47 ± 5 sr at 355 nm and 71 ± 5 sr at 532 nm. A complete ceilometer data processing for a Vaisala CL51 is presented, including the water vapor correction for high latitude for the first time, from sensor provided attenuated backscatter coefficient to particle mass concentration. A combined lidar and sun-photometer approach (based on AERONET products) is applied for mass concentration estimations. Mass concentrations were estimated from both PollyXT and the ceilometer CL51 observations, which were of the order of ~ 30 µg m−3 in the morning and decreased to ~ 20 µg m−3 in the night. A difference of ~ 30% was found between PollyXT and CL51 estimated mass concentrations. The mass retrievals were discussed and compared with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) meteorological and aerosol reanalysis. The inclusion of dust in the retrieved mass concentration slightly improved the correspondence between the observations and the MERRA-2 simulations.

Evidence of the effects of various particle sizes and constituents on blood biomarkers is limited. We performed a panel study with five repeated measurements in 88 healthy college students in Guangzhou, China between December 2017 and January 2018. Mass concentrations of particles with aerodynamic diameters ≤ 2.5 μm (PM2.5), PM1, and PM0.5 and number concentrations of particles with aerodynamic diameters ≤ 200 nm (PN0.2) and PN0.1 were measured. We used linear mixed-effect models to explore the associations of size-fractionated particulate matter and PM2.5 constituents with five blood biomarkers 0-5 days prior to blood collection. We found that an interquartile range (45.9 μg/m3) increase in PM2.5 concentration was significantly associated with increments of 16.6, 3.4, 12.3, and 8.8% in C-reactive protein (CRP), monocyte chemoattractant protein-1 (MCP-1), soluble vascular cell adhesion molecule-1 (sVCAM-1), and endothelin-1(ET-1) at a 5-day lag, respectively. Similar estimates were observed for PM1, PM0.5, PN0.2, and PN0.1. For PM2.5 constituents, consistent positive associations were observed between F- and sVCAM-1 and CRP and between NH4+ and MCP-1, and negative associations were found between Na+ and MCP-1 and ET-1, between Cl- and MCP-1, and between Mg2+ and sVCAM-1. Our results suggested that both particle size and constituent exposure are significantly associated with circulating biomarkers among healthy Chinese adults. Particularly, PN0.1 at a 5-day lag and F- and NH4+ are the most associated with these blood biomarkers.

Existing evidence is scarce concerning the various effects of different PM sizes and chemical constituents on blood lipids. A panel study that involved 88 healthy college students with five repeated measurements (440 blood samples in total) was performed. We measured mass concentrations of particulate matter with diameters ≤ 2.5 μm (PM2.5), ≤1.0 μm (PM1.0), and ≤0.5 μm (PM0.5) as well as number concentrations of particulate matter with diameters ≤ 0.2 μm (PN0.2) and ≤0.1 μm (PN0.1). We applied linear mixed-effect models to assess the associations between short-term exposure to different PM size fractions and PM2.5 constituents and seven lipid metrics. We found significant associations of greater concentrations of PM in different size fractions within 5 days before blood collection with lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A (ApoA1) levels, higher apolipoprotein B (ApoB) levels, and lower ApoA1/ApoB ratios. Among the PM2.5 constituents, we observed that higher concentrations of tin and lead were significantly associated with decreased HDL-C levels, and higher concentrations of nickel were associated with higher HDL-C levels. Our results suggest that short-term exposure to PM in different sizes was deleteriously associated with blood lipids. Some constituents, especially metals, might be the major contributors to the detrimental effects.

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.

Ammonia (NH3), a gasous compound ubiquitiously present in the atmosphere, is involved in the formation of secondary organic aerosol (SOA), but the exact mechanisum is still not well known. This study presents the results of SOA experiments from the photooxidation of α-pinene in the presence of NH3 in the reaction chamber. SOA was formed in nucleation experiment and in seeded experiment with ammonium sulfate particles as seeds. The chemical composition and time-series of compounds in the gas- and particle- phase were characterized by an on-line high-resolution time-of-flight proton transfer reaction mass spectrometer (HR-ToF-PTRMS) and a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), respectively. Our results show that for the aerosol particles in cloud condensation nuclei (CCN) size, the mass concentration of ammonium (NH4+) was still rising even after the mass concentration of organic component started to decrease due to aerosol wall deposition and evaporation, implying the continuous new formation of particle phase ammonium in the process. Stoichiometric neutralization analysis of aerosol indicates that organic acids have a central role in the formation of particle phase ammonium. Our measurements show a good correlation between the gas phase organic mono- and di-carboxylic acids formed in the photooxidation of α-pinene and the ammonium in the particle phase, thus highlighting the contribution of gas-phase organic acids to the ammonium formation in the CCN-size SOA particles. The work shows that the gas-phase organic acids contribute to the SOA formation by forming ammonium salts through acid-base reaction. The changes in aerosol mass, particle size and chemical composition resulting from the NH3-SOA interaction can potentially alter the aerosol direct and indirect forcing and therefore alter its impact on climate change.

Aerosols and their transformation process in atmosphere have significant effects on climate. Transformation process is a complex combination of physical and chemical reactions. Multiple oxidizing agents and other factors, such as radiation, affect the transformation process. Characterization of these factors and their strength is a problem, where advanced methods might help to gain more understanding.In this work, we modeled transformation of wood combustion emission measured in the environmental chamber by using causal modeling (Pearl, 2009). The aim of the study was to use state-of-the-art causal discovery methods to search causal pathways between measured variables: precursors and particle products. The data used in the modelling are introduced in Tiitta et al. (2016).In addition to wood combustion experiments, we simulated artificial datasets to understand abilities of the model. We wanted to evaluate the accuracy of our model to confirm the correct structure between variables and reproduce the measured transformation. This helps us to understand the model performance in real datasets.We found that model could reproduce the measured evolution well. The structure between emission parts was not completely matching to prior assumption. Usually incorrect predictors in the modeled structure are highly correlated with correct causes. References:Pearl, J.: Causality : Models, Reasoning and Inference., Cambridge University Press., 2009.Tiitta et al., Atmos. Chem. Phys., 16, 13251-13269, 2016.

Primary emissions of wood combustion are complex mixtures of hundreds or even over a thousand compounds, which pass through a series of chemical reactions and physical transformation processes in the atmosphere (aging). This aging process depends on atmospheric conditions, such as concentration of atmospheric oxidizing agents (OH radical, ozone and nitrate radicals), humidity and solar radiation, and is known to strongly affect the characteristics of atmospheric aerosols. However, there are only few models that are able to represent the aging of emissions during its lifetime in the atmosphere. In this work, we implemented a model (Model for aging of Emissions in environmental CHAmber, MECHA v 1.0) to describe the evolution by differential equation system. The model performance was first evaluated using two different, simulated datasets. The purpose of the evaluation was to investigate the ability of the model to (1) find the correct relationships between the variables in the dataset and (2) to evaluate the accuracy of the model to reproduce the evolution of variables in time. Subsequently, the model was implemented to wood combustion exhaust in atmosphere, based on a dataset from smog chamber experiments. Evaluation in simulated datasets served as a basis of the drawings made from modeled aging of the residential wood combustion emission. We found that the model was able to reproduce the evolution of the variables in time reasonably well. By using the state of the art detection algorithms for causal structures, we could unveil a large number of relationships for measured variables. However, as the emission data is complex in its nature due to multiple processes interacting with each other, for many relationships it was not possible to say if there was a causal pathway or if the variables were just covarying. This study serves as the first step towards a comprehensive model for the description of the evolution of the whole emission in both gas- and particle phase during atmospheric aging. We present contributions to challenges faced in this kind of modeling and discuss the possible improvements and expected importance of those for the model.

Background: Little information exists on interaction effects between air pollution and influenza vaccination on allergic respiratory diseases. We conducted a large population-based study to evaluate the interaction effects between influenza vaccination and long-term exposure to ambient air pollution on allergic respiratory diseases in children and adolescents.Methods: A cross-sectional study was investigated during 2012-2013 in 94 schools from Seven Northeastern Cities (SNEC) in China. Questionnaires surveys were obtained from 56 137 children and adolescents aged 2-17 years. Influenza vaccination was defined as receipt of the influenza vaccine. We estimated air pollutants exposure [nitrogen dioxide (NO2) and particulate matter with aerodynamic diameters

Background: Ambient air pollution exposure and influenza virus infection have been documented to be independently associated with reduced lung function previously. Influenza vaccination plays an important role in protecting against influenza-induced severe diseases. However, no study to date has focused on whether influenza vaccination may modify the associations between ambient air pollution exposure and lung function.Methods: We undertook a cross-sectional study of 6740 children aged 7-14 years into Seven Northeast Cities (SNEC) Study in China during 2012-2013. We collected information from parents/guardians about sociodemographic factors and influenza vaccination status in the past three years. Lung function was measured using portable electronic spirometers. Machine learning methods were used to predict 4-year average ambient air pollutant exposures to nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter < 1 mu m (PM1), < 2.5 mu m (PM2.5) and < 10 mu m (PM10). Two-level linear and logistic regression models were used to assess interactions between influenza vaccination and long-term ambient air pollutants exposure on lung function reduction, controlling for potential confounding factors.Results: Ambient air pollution were observed significantly associated with reductions in lung function among children. We found significant interactions between influenza vaccination and air pollutants on lung function, suggesting greater vulnerability to air pollution among unvaccinated children. For example, an interaction (p(interaction) = 0.002) indicated a - 283.44 mL (95% CI: - 327.04, - 239.83) reduction in forced vital capacity (FVC) per interquartile range (IQR) increase in PK_ concentrations among unvaccinated children, compared with the -108.24 mL (95%CI: - 174.88, - 41.60) reduction in FVC observed among vaccinated children. Results from logistic regression models also showed stronger associations between per IQR increase in PM1 and lung function reduction measured by FVC and peak expiratory flow (PEF) among unvaccinated children than the according ORs among vaccinated children [i.e., Odds Ratio (OR) for PM1 and impaired FVC: 2.33 (95%CI: 1.79, 3.03) vs 1.65 (95%CI: 1.20, 2.28); OR for PM2.5 and impaired PEF: 1.45 (95%CI: 1.12,1.87) vs 1.04 (95%CI: 0.76,1.43)]. The heterogeneity of the modification by influenza vaccination of the associations between air pollution exposure and lung function reduction appeared to be more substantial in girls than in boys.Conclusion: Our results suggest that influenza vaccination may moderate the detrimental effects of ambient air pollution on lung function among children. This study provides new insights into the possible co-benefits of strengthening and promoting global influenza vaccination programs among children.

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.

Background and objectives: Little is known about PM1 effects on respiratory health, relative to larger size fractions (PM2.5). To address this literature gap, we assessed associations between PM1 exposure and asthmatic symptoms in Chinese children and adolescents, compared with PM2.5. Methods: A total of 59,754 children, aged 2–17 years, were recruited from 94 kindergartens, elementary and middle schools in the Seven Northeast Cities (SNEC) study, during 2012–2013. We obtained information on asthma and asthma-related symptoms including wheeze, persistent phlegm, and persistent cough using a standardized questionnaire developed by the American Thoracic Society. PM1 and PM2.5 concentrations were estimated using a spatial statistical model matched to the children's geocoded home addresses. To examine the associations, mixed models with school/kindergarten as random intercept were used, controlling for covariates. Results: Odds ratios (ORs) of doctor-diagnosed asthma associated with a 10-μg/m3 increase for PM1 and PM2.5 were 1.56 (95% CI: 1.46–1.66) and 1.50 (1.41–1.59), respectively, and similar pattern were observed for other outcomes. Interaction analyses indicated that boys and the individuals with an allergic predisposition may be vulnerable subgroups. For example, among children with allergic predisposition, the ORs for doctor diagnosed asthma per 10 μg/m3 increase in PM1 was 1.71 (95% CI: 1.60–1.83), which was stronger than in their counterparts (1.46; 1.37–1.56) (p for interaction

Evidence on the associations between airborne particulates of diameter ≤1 μm (PM 1 ) and airborne particulates of diameter ≤2.5 μm (PM 2.5 ) and childhood blood pressure (BP) is scarce. To help to address this literature gap, we conducted a study to explore the associations in Chinese children. Between 2012 and 2013, we recruited 9354 children, aged 5 to 17 years, from 62 schools in 7 northeastern Chinese cities. We measured their BP with a mercury sphygmomanometer. We used a spatiotemporal model to estimate daily ambient PM 1 and PM 2.5 exposures, which we assigned to participants’ home addresses. Associations between particulate matter exposure and BP were evaluated with generalized linear mixed regression models. The findings indicated that exposure to each 10 mg/m 3 greater PM 1 was significantly associated with 2.56 mm Hg (95% CI, 1.47–3.65) higher systolic BP and 61% greater odds for hypertension (odds ratio=1.61 [95% CI, 1.18–2.18]). PM 1 appears to play an important role in associations reported between PM 2.5 exposure and BP, and we found that the ambient PM 1 /PM 2.5 ratio (range, 0.80–0.96) was associated with BP and with hypertension. Age and body weight modified associations between air pollutants and BP ( P 1 is associated with hypertension in children, and that PM 1 might be a leading contributor to the hypertensive effect of PM 2.5 . Researchers and policy makers should pay closer attention to the potential health impacts of PM 1 .

Interactions between anthropogenic and biogenic emissions, and implications for aerosol production, have raised particular scientific interest. Despite active research in this area, real anthropogenic emission sources have not been exploited for anthropogenic-biogenic interaction studies until now. This work examines these interactions using α-pinene and pellet boiler emissions as a model test system. The impact of pellet boiler emissions on secondary organic aerosol (SOA) formation from α-pinene photo-oxidation was studied under atmospherically relevant conditions in an environmental chamber. The aim of this study was to identify which of the major pellet exhaust components (including high nitrogen oxide (NOx), primary particles, or a combination of the two) affected SOA formation from α-pinene. Results demonstrated that high NOx concentrations emitted by the pellet boiler reduced SOA yields from α-pinene, whereas the chemical properties of the primary particles emitted by the pellet boiler had no effect on observed SOA yields. The maximum SOA yield of α-pinene in the presence of pellet boiler exhaust (under high-NOx conditions) was 18.7% and in the absence of pellet boiler exhaust (under low-NOx conditions) was 34.1%. The reduced SOA yield under high-NOx conditions was caused by changes in gas-phase chemistry that led to the formation of organonitrate compounds.

This cross-sectional study evaluates the association of air pollution exposure and having been breastfed or not with lung function among children in China., Key Points Question Is having been breastfed associated with lower risk of impaired lung function in children exposed to ambient air pollution? Findings In this cross-sectional study of 6740 Chinese children aged 7 to 14 years, exposure to greater concentrations of particulate matter air pollution was associated with higher rates of lung function impairment among children who had not been breastfed compared with those who had been breastfed. Meaning These findings suggest that breastfeeding is associated with lower risk of lung function impairment among children exposed to ambient air pollutants., Importance Breastfeeding and exposure to ambient air pollutants have been found to be independently associated with respiratory health in children; however, previous studies have not examined the association of breastfeeding as a potential moderator of the association. Objective To assess associations of breastfeeding and air pollution with lung function in children. Design, Setting, and Participants Using a cross-sectional study design, children were recruited from 62 elementary and middle schools located in 7 Chinese cities from April 1, 2012, to October 31, 2013. Data analyses were conducted from November 1, 2018, to March 31, 2019. Exposures Long-term concentrations of airborne particulate matter with a diameter of 1 μm or less (PM1), airborne particulate matter with a diameter of 2.5 μm or less (PM2.5), airborne particulate matter with a diameter of 10 μm or less (PM10), and nitrogen dioxide were estimated using a spatial statistical model matched to children’s geocoded home addresses, and concentrations of PM10, sulfur dioxide, nitrogen dioxide, and ozone were measured by local air monitoring stations. Main Outcomes and Measures Breastfeeding was defined as maternal report of having mainly breastfed for longer than 3 months. Lung function was measured using portable electronic spirometers. Using previously published predicted spirometric values for children in Northeast China as the reference, lung impairment was defined as forced vital capacity (FVC) less than 85%, forced expiratory volume in the first second of expiration less than 85%, peak expiratory flow less than 75%, or maximum midexpiratory flow less than 75%. Results Participants included 6740 children (mean [SD] age, 11.6 [2.1] years; 3382 boys [50.2%]). There were 4751 children (70.5%) who were breastfed. Mean (SD) particulate matter concentrations ranged from 46.8 (6.5) μg/m3 for PM1 to 95.6 (9.8) μg/m3 for PM10. The prevalence of lung function impairment ranged from 6.8% for peak expiratory flow to 11.3% for FVC. After controlling for age, sex, and other covariates, 1–interquartile range greater concentration of pollutants was associated with higher adjusted odds ratios (AORs) for lung function impairment by FVC among children who were not breastfed compared with those who were (PM1: AOR, 2.71 [95% CI, 2.02-3.63] vs 1.20 [95% CI, 0.97-1.48]; PM2.5: AOR, 2.27 [95% CI, 1.79-2.88] vs 1.26 [95% CI, 1.04-1.51]; and PM10: AOR, 1.93 [95% CI, 1.58-2.37] vs 1.46 [95% CI, 1.23-1.73]). Younger age (

The fraction of gasoline direct injection (GDI) vehicles comprising the total vehicle pool is projected to increase in the future. However, thorough knowledge about the influence of GDI engines on important atmospheric chemistry processes is missing—from their contribution to secondary organic aerosol (SOA) precursor emissions, SOA formation, and potential role in biogenic-anthropogenic interactions. The objectives of this study were to 1) characterize emissions from modern GDI vehicle and investigate their role in SOA formation chemistry and 2) investigate biogenic-anthropogenic interactions related to SOA formation from a mixture of GDI vehicle emissions and a model biogenic compound, α-pinene. Specifically, we studied SOA formation from modern GDI vehicle emissions during the constant load driving. In this study we show that SOA formation from GDI vehicle emissions was observed in each experiment. VOCs measured with the PTR-ToF-MS could account for 19−42% of total SOA mass generated in each experiments. This suggests there were lower volatility intermediate-VOCs (IVOCs) and semi-VOCs (SVOCs) in the GDI exhaust that likely contributed to SOA production but were not detected with the instrumentation used in this study. This study also demonstrates that two distinct mechanisms caused by anthropogenic emissions suppress α-pinene SOA mass yield. The first suppressing effect was the presence of NOx. This mechanism is consistent with previous reports demonstrating suppression of biogenic SOA formation in the presence of anthropogenic emissions. Our results imply that the second suppressing effect was the presence of anthropogenic gas-phase species that suppressed biogenic SOA formation by changing the gas-phase chemistry of α-pinene. This change in oxidation pathways led to formation of α-pinene oxidation products that most likely do not have vapor pressures low enough to partition into the particle phase. Overall, the presence of gasoline vehicle exhaust caused more than 50 % suppression in α-pinene SOA mass yield compared to the α-pinene SOA mass yield measured in the absence of an anthropogenic influence.

Aerosols emitted from various anthropogenic and natural sources undergo constant physicochemical transformations in the atmosphere, altering their impacts on health and climate. This article presents the design and characteristics of a novel Photochemical Emission Aging flow tube Reactor (PEAR). The PEAR was designed to provide sufficient aerosol mass and flow for simultaneous measurement of the physicochemical properties of aged aerosols and emission exposure studies (in vivo and in vitro). The performance of the PEAR was evaluated by using common precursors of secondary aerosols as well as combustion emissions from a wood stove and a gasoline engine. The PEAR was found to provide a near laminar flow profile, negligible particle losses for particle sizes above 40 nm, and a narrow residence time distribution. These characteristics enable resolution of temporal emission patterns from dynamic emission sources such as small-scale wood combustion. The formation of secondary organic aerosols (SOA) in the PEAR was found to be similar to SOA formation in a smog chamber when toluene and logwood combustion emissions were used as aerosol sources. The aerosol mass spectra obtained from the PEAR and smog-chamber were highly similar when wood combustion was used as the emission source. In conclusion, the PEAR was found to plausibly simulate the photochemical aging of organic aerosols with high flow rates, needed for studies to investigate the effects of aged aerosols on human health. The method also enables to study the aging of different emission phases in high time resolution, and with different OH-radical exposures up to conditions representing long-range transported aerosols. Copyright © 2019 American Association for Aerosol Research

Background: There is scarcity of evidence on the associations between greenness and blood pressure, particularly in children. We aimed to investigate this association among children living in China. Methods: Our study included 9,354 children (4·3 to 17·8 years of age) participating in the Seven Northeastern Cities Study in China. Greenness around each child's school was estimated by NDVI (Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index). Particulate matter

Background: It is unknown whether giving birth via caesarean section (c-section) is a modifier for the association between air pollution and asthma. Methods: From 2012 to 2013, 59,754 children between the ages of 2 and 17 were randomly selected from 94 middle schools, elementary schools and kindergartens in seven Chinese cities for a cross-sectional study. The children's parents or guardians completed questionnaires, from which data on asthma as well as asthma-related symptoms were obtained. Participants' exposure to particles with an aerodynamic diameter ≤1·0μm (PM1), ≤2·5μm (PM2·5), and ≤10μm (PM10) and exposure to nitrogen dioxide (NO2) were estimated using random forest models. We used two-level logistic regressions and added an interaction term between mode of delivery and ambient air pollution into the model to estimate effect modification from c-sections after appropriate adjustments for potential confounding variables. Findings: Among children delivered by c-section, the adjusted ORs for asthma and its symptoms per 10 μg/m3 air pollutant increase (1·14 95% CI: 1·09-1·19 to 2·10 95% CI: 1·88-2·34) were significantly higher than those of children delivered vaginally (1·04 95% CI: 0·97-1·13 to 1·38 95%CI: 1·23-1·55). The interactions between c-sections and ambient air pollution were statistically significant for all studied respiratory disorders, except current wheeze. Interpretation: Delivery via c-section appears to increase the risks of air pollution on asthma and its symptoms in our study population of Chinese children. Funding Statement:This work was supported by the National Natural Science Foundation of China (81872582, 91543208, 81872583, 81673128, and 81703179), the National Key Research and Development Program of China (2018YFE0106900), the Guangdong Provincial Natural Science Foundation Team Project (2018B030312005), the Guangdong Province Natural Science Foundation (2017A050501062, and 2018B05052007), and the Fundamental Research Funds for the Central Universities (19ykjc01). Declaration of Interests: The authors declare no competing interest. Ethics Approval Statement: The study was designed and conducted in accordance with the World Medical Association’s Declaration of Helsinki Ethical Principles for Medical Research Involving Human Subjects. The Human Studies Committee of Sun Yat-sen University, Guangzhou, China approved this study. After approval was obtained from each school’s principal, parents or guardians of children were invited to take part in information sessions where consent form was signed and questionnaires were completed

It is unknown whether giving birth via caesarean section (c-section) is a modifier for the association between air pollution and asthma. From 2012 to 2013, 59,754 children between the ages of 2 and 17 were randomly selected from 94 middle schools, elementary schools and kindergartens in seven Chinese cities for a cross-sectional study. The children's parents or guardians completed questionnaires, from which data on asthma as well as asthma-related symptoms were obtained. Participants' exposure to particles with an aerodynamic diameter ≤1.0 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10) and exposure to nitrogen dioxide (NO2) were estimated using random forest models. We used mixed effects logistic regression models and added an interaction term between mode of delivery and ambient air pollution into the model to estimate effect modification from c-sections after appropriate adjustments for potential confounding variables. Among children delivered by c-section, the adjusted ORs for asthma and its symptoms per interquartile range (IQR) increase of PM1, PM2.5, PM10 and NO2 (1.20 95% CI: 1.07-1.34 to 2.04 95% CI: 1.87-2.24) were significantly higher than those of children delivered vaginally (1.05 95% CI: 0.92-1.19 to 1.33 95%CI: 1.21-1.47). The interactions between c-sections and ambient air pollution were statistically significant for all studied respiratory disorders, except current wheeze. Delivery via c-section may increase the risks of air pollution on asthma and its symptoms in Chinese children.

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