Low-level clouds play a crucial role in the Arctic climate system, for example by contributing to surface warming. Although many efforts have been made to investigate low-level clouds, there is still a significant in-situ data gap within the atmospheric boundary layer (ABL) and the lower troposphere. While long-term ground-based observatories provide valuable continuous measurements, they cannot resolve the vertical structure of aerosols and clouds.To address this data gap, five uncrewed aerial systems (UAS) were deployed during two intensive measurement campaigns at the Pallas Atmosphere-Ecosystem Supersite in northern Finland in spring (4–12 April 2025) and autumn (16–30 September 2025). Fixed-wing, vertical take-off and landing (VTOL), and multirotor platforms were operated jointly by the Finnish Meteorological Institute (FMI) and the Technische Universität Braunschweig. In total, 246 measurement flights were conducted, reaching altitudes of up to 2 km above ground level and conducting over 80 hours of in-situ sampling.The UAS were equipped with different sensors to measure aerosols, including two condensation particle counters with different cut-offs to measure the aerosol particle number concentration, a Partector 2 Pro to measure the size distribution between 10 and 300 nm and a POPS to measure the size distribution between 115 and 3370 nm. In addition meteorological parameters, and cloud droplet properties were also measured. This enables a detailed characterization of the vertical distribution of aerosols and their interaction with the ABL and low-level clouds. These measurements were compared to long-term observations from the nearby ground-based observatory Sammaltunturi. This study demonstrates the value of combining ground-based measurements with UAS profiling when investigating aerosol-cloud interactions.Preliminary results indicate pronounced seasonal differences. Spring conditions were dominated by new particle formation events associated with long-range air mass transport from the central Arctic. In contrast, autumn measurements were strongly influenced by low-level cloud formation and local aerosol sources. Overall, this campaign demonstrates the added value of UAS observations in improving the understanding of aerosol-cloud interactions in the sub-Arctic and enhancing the interpretability of existing ground-based datasets.

A dataset of in situ observations of stratus cloud microphysics was created from measurements performed at the Pallas atmosphere-ecosystem super site during the Pallas Cloud Experiment (PaCE) in autumn 2022. The data were collected using a small uncrewed aircraft (SUA) and the low-cost, lightweight Universal Cloud and Aerosol Sounding System UCASS,. Data from the instrument - platform combination was previously validated in during a similar field campaign at the same site. These measurements are intended to expand on the previous campaign since they form an extended dataset with the uncertainties already evaluated by previous experimental work. The dataset contains cloud droplet size distribution, number concentration, and mass concentration, in addition to geolocation data, and meteorological variables. The flight pattern of the SUA was planned to provide a quasi-vertical profile. A total of 84 of these profiles across 39 flights were performed during the campaign period. The data from the SUA flights are available from 10.5281/zenodo.14756233 .

In the polar regions, the extreme cold and dark atmosphere of the winter season imposes stringent conditions on the planetary boundary layer (PBL) leading to limited vertical atmospheric mixing and increasing the severity of air pollution episodes. Understanding the physical and chemical transformations affecting air pollution critically depends on our ability to accurately describe the dynamics of the PBL. This requires an adequate combination of modeling, ground-based observations, and vertical profile measurement systems to assess emission dispersion and transport in stratified environments. We present an overview of the meteorological conditions and PBL observations collected during the Alaskan Layered Pollution and Chemical Analysis (ALPACA) field experiment in Fairbanks, Alaska, in winter 2022. Surface and vertical profile observations of radiation, turbulence, dynamics, and atmospheric composition were collected to account for surface and elevated emissions. The study area is the Tanana Valley in the interior of Alaska, which experiences persistent synoptic anticyclonic conditions resulting in stagnant flow and limited ventilation, exacerbating air pollution levels. These conditions are interspersed with periodic transits of cyclonic air masses influencing the PBL through radiative forcing that erodes low-level temperature inversion layers and mixes local air masses into the free troposphere. This paper highlights the research objectives, experimental findings, and first results linking meteorological conditions with the observed structure and composition of the PBL under the challenging experimental conditions of the Alaskan winters. It also highlights the need for integrated surface and profiling observations of PBL dynamics and composition, which are critical for advancing across-scale modeling and enhancing predictive capabilities for air pollution episodes locally and throughout the Arctic air shed. SIGNIFICANCE STATEMENT: This article provides an overview of the meteorology during the Alaskan Layered Pollution and Chemical Analysis (ALPACA)-2022 winter field experiment. It also presents observations designed to better understand the physical processes influencing the planetary boundary layer (PBL) and their role in wintertime Arctic air pollution. It describes the synoptic meteorological conditions throughout the experiment and the diverse instrumental platforms used to study the dynamics and composition of the Arctic polluted PBL for the first time. The article emphasizes the importance of multi-instrumental platforms to improve understanding of the PBL composition and dynamics in the context of Arctic air pollution. This is particularly relevant in conditions with limited photochemistry and in areas experiencing very cold, stable environments that exacerbate pollution levels. The observations are used to improve meteorological and air quality model simulations.

Abstract. Aerosol, cloud droplet, and meteorological measurements were carried out by the Finnish Meteorological Institute's payload onboard the tethered balloon systems during the Pallas Cloud Experiment 2022 in Finland. This dataset includes 21 flights between September 16th and October 10th. The observations include vertical profiles and time series of aerosol number concentration and size distribution; cloud droplet number concentration and size distribution; and meteorological parameters. This dataset has been uploaded to the common Zenodo PaCE 2022 community archive (https://zenodo.org/communities/pace2022/, last access: Jan 20, 2025). This dataset (Le et al., 2026) is available at: https://doi.org/10.5281/zenodo.18432043.

Particle linear depolarization ratio is a widely used parameter in lidar research to distinguish different aerosol types and the thermodynamic phase of water. It is most frequently measured at ultraviolet and visible wavelengths (355 and 532 nm), yet multi-wavelength observations suggest that this parameter can vary substantially with wavelength. In this work, we assessed particle linear depolarization ratios at 1565 nm using Halo Photonics StreamLine Doppler lidars. We examined the depolarization ratio through three case studies featuring extremely fresh and aged smoke, and volcanic ash aerosol particles in the troposphere. Both fresh and aged smoke aerosol particles induced low values. Specifically, aerosol layers dominated by extremely fresh smoke showed a depolarization ratio of 0.017 ± 0.004, whereas aged long-range transported smoke particles exhibited marginally higher values. Volcanic aerosol layers induced high depolarization ratios with layer mean values of 0.45 ± 0.01. For the extremely fresh smoke case, we further estimated the smoke mass concentration using the lidar observations at 1565 nm and found good agreement with the in situ observations. These results demonstrate that Halo Doppler lidars operating at 1565 nm wavelength are capable of distinguishing several key aerosol types, enabling a comprehensive characterization of atmospheric conditions by simultaneously observing aerosol properties and wind dynamics.

Central Asia is a region with high-altitude mountains, hosting numerous glaciers and widespread seasonal snow cover, both of which play an integral role in the regional hydrological cycle. Despite their importance, observations of cryospheric and atmospheric variables are scarce in this area but are essential to assess the temporal and spatial changes induced by climate change. To address this gap, we present a diverse data set of cryospheric and atmospheric variables from the Zarafshon River Basin and the Hydrographic Party Glacier (GGP) in Tajikistan, spanning 2018–2025. The dataset includes glacier terminus positions and snow conditions, glacier ablation, high resolution aerial photography, meteorological variables, surface reflectance combined with snow chemistry, and atmospheric aerosol concentrations. These observations provide a valuable basis for research on glacier dynamics, snow processes, and atmosphere-cryosphere interactions in a region where monitoring has been sparse. The data are available at the Finnish Meteorological Institute data repository METIS: https://doi.org/10.57707/fmi-b2share.t4vwg-gf542 (Svensson et al., 2026).

This data paper presents an overview of the cloud spectrometers deployed during the Pallas Cloud Experiment (PaCE) in autumn 2022, a coordinated measurement campaign in the Finnish subarctic that took place between 12 September and 15 December 2022. Four cloud spectrometers – the Cloud and Aerosol Spectrometer (CAS); the Forward Scattering Spectrometer Probe (FSSP-100); the Cloud Droplet Analyzer (CDA); and ICEMET – were operated as ground-based setups, providing high-resolution in-cloud measurements of droplet size distributions and key microphysical properties, such as number concentration (Nc), liquid water content (LWC), median volume diameter (MVD), and effective diameter (ED). The dataset is complemented by meteorological observations of temperature, humidity, wind speed, and visibility at a 1 min resolution. The measurements collected during PaCE 2022 offer valuable insights into aerosol–cloud interactions and cloud evolution in subarctic cloud systems. This dataset is suitable for researchers in cloud microphysics, atmospheric science, and climate modeling, as well as for instrument calibration and validation in future campaigns. The data can also be integrated with complementary concurrent in situ aerosol, remote sensing, UAV, and balloon-borne observations during PaCE 2022 to provide a more comprehensive understanding of cloud microphysics and atmospheric processes in the subarctic environment. The dataset is publicly available at https://doi.org/10.5281/zenodo.15045294 (Doulgeris et al., 2025).

A novel filter-based sampler was deployed during the Pallas Cloud Experiment (PaCE) 2022 for a one-month period in September and October 2022 in Finnish Lapland around 5 km north of the Sammaltunturi station. This area frequently features low-level clouds during autumn. The sampler was deployed on-board of an uncrewed aerial vehicle (UAV) and on the ground. Two filters were deployed simultaneously on the ground and on the UAV to enable a comparison between the two vertical levels. The dataset contains 9 ice-nucleating particle (INP) concentration spectra that feature a temporal overlap at both altitudes, a handling blank filter to assess possible contamination during handling and additional samples from both setups without the temporal overlap. The dataset is the first of its kind, providing altitude-based INP concentrations in Finnish Lapland, and is available at the Zenodo Open Science data archive (https://doi.org/10.5281/zenodo.13911633, Böhmländer et al., 2024). There is no clear systematic difference between INP concentrations measured at the different altitudes. The INP concentration is variable over the period measured and also does show some differences on the vertical level. The INP concentration at 253 K varies between 0.15 and 3.06 Lstd-1 on the ground, and between 0.48 and 1.69 Lstd-1 at higher altitudes. The connection to synoptic conditions and ambient measurements might provide a better understanding of the origin, lifetime, and distribution of INPs in Finnish Lapland.

Primary biological aerosol particles (PBAPs), including fungal spores, bacteria and pollen grains, are widely distributed in the atmosphere. Some PBAPs are highly efficient ice nucleating particles (INPs), but their impact on atmospheric ice formation is currently uncertain. PBAPs have been associated with INPs that are active at high sub-zero temperatures and may contribute disproportionally high in places with little anthropogenic influence, such as the high Arctic [1] and in the boreal forest [2].This study investigates PBAPs and INPs in the pristine Finnish sub-Arctic at the Pallas supersite from September 2022 to September 2023. To study PBAPs, we combine measurements of highly fluorescent aerosol particles (HFAPs) with the Wideband Integrated Bioaerosol Sensor (WIBS) [3], fungal spore counts from a Hirst-type volumetric sampler and eDNA sequence analysis from filter samples. We compare PBAPs to INP measurements over a wide temperature range using the Portable Ice Nucleation Experiment (PINE) [4] and the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT) [2].We found a strong seasonal trend of a subset of HFAPs with maximum concentrations in summer and an abrupt and strong decrease with snow cover. Together with an exponential relationship with temperature, this suggests locally emitted bioaerosols. The measured bioaerosols show a positive correlation with INPs active over a wide activation temperature range (-31°C - -8°C). An exceptionally high correlation (r=0.94, p

The Portable Ice Nucleation Experiment (PINE) was deployed during the Pallas Cloud Experiment (PaCE) 2022 for a three-month-period at the Sammaltunturi station in autumn 2022 (between late September 2022 and late December 2022). The station is located on top of a hill on the edge between sub-Arctic and boreal forest environments, typically receiving air masses from the Arctic and the south. Since clouds are frequently present at the station during autumn, the present aerosol particles can have a direct impact on cloud properties. Ice-nucleating particles (INPs) are aerosol particles that facilitate primary ice nucleation in supercooled cloud droplets. The PINE measured the INP concentration with a high temporal resolution of six minutes at different nucleation temperatures between 240 and 252 K. The INP concentration varied exponentially with the freezing temperature and differences between different months were observed. The highest median INP concentration was measured during December over the whole temperature range, while during November the lowest median INP concentration was measured. The data presented here is useful to study aerosol-cloud interactions for a sub-Arctic location with minimal anthropogenic influence. The high temporal resolution allows to correlate the INP concentration with other measurements, such as size distribution data and meteorological data. In addition, the data provides the ice nucleating ability of ambient aerosol particles, which can be combined with models to study the nature, the source and the age of the INPs.

The study presents drone-based measurements to investigate the seasonal vertical variability of equivalent black carbon (eBC) mass and particle number concentrations (PNC) at a rural and urban site in the Czech Republic. Vertical profiles of eBC were measured using a micro-aethalometer, while PNC was measured using an optical particle counter. Drone-based eBC measurements closely matched reference aethalometers placed at both ground level and at 230 m of a tower when using a humidity control mechanism. Without dryer, eBC mass concentration was overestimated by 276 % in summer and 285 % in winter, but uncertainties were reduced to under 10 % with drying. These findings highlight the importance of humidity control for accurate aerosol measurements, especially for eBC. The study also revealed a decrease in eBC and PNC with height at the rural site during both summer and winter, with seasonal differences in the altitude where this decrease began. Elevated eBC concentrations in winter were due to increased atmospheric stability and combustion-related fine particles. At the urban site, concentrations in summer were uniform with height (4 to 100 m above ground level (a.g.l.)) but gradually decreased with height during winter. Furthermore, the study investigated changes in the vertical distribution of eBC and PNC during a high pollution event at the urban site, influenced by long-range transport. Our findings confirm the effectiveness of drones in capturing vertical variations of air pollutants, offering results on the dynamics between local emissions, atmospheric stability, and long-range transport and suggesting the necessity of measuring vertical concentration profiles to support air quality management strategies.

A mobile sampler for collecting aerosol particles on an uncrewed aerial vehicle (UAV) was developed and tested during three consecutive Pallas cloud experiment campaigns in the vicinity of the Sammaltunturi Global Atmosphere Watch site (67 degrees 58 ' N, 24 degrees 7 ' E, 565 m above sea level) in Finland. The sampler is designed to collect aerosol particles onto Nuclepore filters, which are subsequently analysed for the temperature-dependent number concentration of ice-nucleating particles (INPs) of the sampled aerosol using a freezing assay. The sampler was flown with a fixed-wing UAV in different altitudes up to 1000 m above ground level (a.g.l). The total flight times ranged from 60 min to around 100 min, depending on environmental conditions. Pressure, temperature and relative humidity were also measured to provide information about the meteorological flight conditions. The flow over the filter was maintained by a micro-diaphragm pump, providing approximately 10 standard litres per minute over a small filter (diameter of 25 mm) and around 11 standard litres per minute over a larger filter (diameter of 47 mm) at a pressure corresponding to 500 m above sea level. For a typical flight time of 1.5 h, this results in a sampled air volume of approximately 930 to 1000 standard litres per flight, giving an INP detection limit of approximately 1.1x10-3 and 1.0x10-3 INPs per standard litre, respectively. For comparison to the flight results, a similar set-up was deployed at ground level. The comparison shows a clear distinction from the water and handling blank background for both set-ups, proving the technical feasibility of the set-ups. Furthermore, for some flights, a shift between the two INP populations can be seen, indicating that ground-based INP measurements deviate from the samples collected on board the UAV.

Fluorescent aerosol particles (FAPs), as a fraction of total aerosol particles (TAPs), were measured online with a Wideband Integrated Bioaerosol Sensor 5/NEO (WIBS, Droplet Measurement Technologies) from mid-September to mid-December during the Pallas Cloud Experiment 2022 (PaCE22) at the station of Sammaltunturi, located in the sub-Arctic region of Finnish Lapland. The WIBS measures particle size distributions from 0.5 to 30 mu m and fluorescence in three channels of single aerosol particles, as well as particle concentrations. Since biological aerosol particles can exhibit intrinsic fluorescence, FAP concentration can be used as a proxy for primary biological aerosol particles (PBAPs) like bacteria, fungal spores and pollen. The concentrations and size distributions of different fluorescent particles, together with meteorological data and air mass trajectories, allow valuable insights into the emission of PBAPs from northern boreal forests and their dynamic in the atmosphere. We found a clear seasonal trend for most FAP types and a strong, sudden decrease in concentration after the surrounding ground is covered in snow. Caution should be taken in interpreting the data as interference may be introduced by non-biological fluorescent particles like secondary organic aerosols or soot, as well as biological secondary organic aerosols.

A three-month air quality measurement campaign was conducted in spring 2023 near a busy highway in Espoo, Finland. The measurement site featured a high (6.5 m) noise barrier built adjacent to the highway. Additionally, there was a gap in the noise barrier at the selected measurement site, providing an opportunity to study the air quality impacts of the noise barrier. Several air quality measurement devices were installed behind the noise barrier and in the gap at distances of 10, 20 and 40 m from the side of the highway. Additionally, 15 passive samplers were deployed to monitor NO2 concentrations across the study area, mobile measurements were conducted using the ATMo-Lab mobile laboratory on the highway, and concurrent flights with drones equipped with AQ monitors were performed along the highway. The effects of the noise barrier on PM10, PM2.5, lung deposited surface area (LDSA), particle number concentration (PNC), NO2, and black carbon (BC) were quantified based on the analysed measurement data. Furthermore, the measurements were compared with simulated pollutant concentrations from a local-scale Gaussian air quality model (Enfuser) with a nearby obstacle detection and concentration reduction method incorporated in the model to address the effects of the noise barrier in the study. The noise barrier was found to effectively reduce pollutant concentrations behind the barrier. The most notable reductions were observed closest to the highway. The greatest reductions were observed for PM10 (mostly road dust) while gaseous concentrations, such as NO2, exhibited less pronounced decreases.

A lightweight, custom-built drone backpack for air quality and atmospheric state variable measurements, mounted on top of consumer-grade drone, was used during the Pallas Cloud Experiment (PaCE) campaign's intensive operation period (IOP) between 12 September and 10 October 2022. The drone backpack measurements include 63 vertical profile flights from two close by locations at Pallasj & auml;rvi lake and 12 intercomparison flights against reference instrumentation at Sammaltunturi station. The observations include aerosol number concentrations and size distributions and meteorological parameters (temperature, relative humidity, pressure, and wind speed and direction) up to 500 m above ground level. The dataset has been uploaded to the common Zenodo PaCE 2022 community archive (https://zenodo.org/communities/pace2022/, last access: 5 June 2025). The datasets are available in two formats, NetCDF and CSV, from 10.5281/zenodo.14780929 (Brus et al. 2025a) and 10.5281/zenodo.14778421 (Brus et al. 2025b), respectively.

Primary biological aerosol particles (PBAPs) can influence weather and climate by acting as high-temperature ice nucleating particles (INPs), especially in clean, rural regions like the European sub-Arctic. However, the actual contribution to atmospheric ice nucleation and the exact identity of PBAPs serving as INPs remain poorly understood. Here, we present measurements of INPs and highly fluorescent aerosol particles (HFAPs) over the course of 1 year at the Pallas Atmosphere-Ecosystem Supersite in the Finnish sub-Arctic, aiming to determine whether PBAPs significantly contribute to atmospheric INPs and to identify which types do so. Our findings indicate that certain HFAPs are strongly influenced by meteorological variables, with high concentrations occurring when the station is within the atmospheric mixing layer, suggesting local biological sources. These HFAPs are the main contributors to high-temperature INPs, with an exceptionally strong correlation (r = 0.94, p < 0.0001) between HFAP concentrations and INPs active at -13.5 degrees C. For the first time, to the best of our knowledge, we combine INP and HFAP data with direct fungal spore counts and environmental DNA (eDNA) analysis to determine the biological origins of HFAPs and INPs. The results suggest that most high-temperature INPs are likely fungal spores. eDNA analysis further reveals that airborne fungi are dominated by Basidiomycota and that only a small fraction of the detected fungal genera have, to date, been tested for ice nucleation activity (INA) according to the literature. Among those reported in the literature, most exhibit very low or no INA. This underscores the significant knowledge gap in our understanding of biological ice nucleation in the atmosphere.

The Alaskan Layered Pollution And Chemical Analysis (ALPACA) field experiment was a collaborative study designed to improve understanding of pollution sources and chemical processes during winter (cold climate and low-photochemical activity), to investigate indoor pollution, and to study dispersion of pollution as affected by frequent temperature inversions. A number of the research goals were motivated by questions raised by residents of Fairbanks, Alaska, where the study was held. This paper describes the measurement strategies and the conditions encountered during the January and February 2022 field experiment, and reports early examples of how the measurements addressed research goals, particularly those of interest to the residents. Outdoor air measurements showed high concentrations of particulate matter and pollutant gases including volatile organic carbon species. During pollution events, low winds and extremely stable atmospheric conditions trapped pollution below 73 m, an extremely shallow vertical scale. Tethered-balloon-based measurements intercepted plumes aloft, which were associated with power plant point sources through transport modeling. Because cold climate residents spend much of their time indoors, the study included an indoor air quality component, where measurements were made inside and outside a house to study infiltration and indoor sources. In the absence of indoor activities such as cooking and/or heating with a pellet stove, indoor particulate matter concentrations were lower than outdoors; however, cooking and pellet stove burns often caused higher indoor particulate matter concentrations than outdoors. The mass-normalized particulate matter oxidative potential, a health-relevant property measured here by the reactivity with dithiothreiol, of indoor particles varied by source, with cooking particles having less oxidative potential per mass than pellet stove particles.