This paper presents a new user-friendly version of the Atmospheric Radon MONitor (ARMON). The efficiency of the instrument is of 0.0057 s^-1, obtained using different techniques at Spanish and German chambers. The total calculated uncertainty of the ARMON for hourly radon concentrations above 5 Bq m^-3 is lower than 10 % (k = 1). Results confirm that the ARMON is suitable to measure low-level radon activity concentrations and to be used as a transfer standard to calibrate in situ radon monitors.

In this paper, we further optimize the measurement of atmospheric organosulfates by hydrophilic interaction liquid chromatography (HILIC), offering an improved method for quantifying and speciating atmospheric organosulfates. These efforts will contribute to a deeper understanding of secondary organic aerosol precursors, formation mechanisms, and the contribution of organosulfate to atmospheric aerosols, ultimately guiding research in the field of air pollution prevention and control.

We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.

Accurate global wind estimation is crucial for weather prediction and environmental modeling. Our study investigates a method to refine atmospheric motion vectors (AMVs) by comparing them with high-precision active-sensor winds. Leveraging supervised learning, we discovered that using high-precision active-sensor data can significantly reduce biases in passive-sensor winds in addition to providing estimates of the wind errors, thereby improving their reliability.

This study showcases the use of a compact elastic lidar to monitor aerosols aboard moving platforms. By coupling dual-wavelength and depolarization measurements with photometer data, we studied aerosols during events of Saharan dust and smoke transport. Our research, conducted in various scenarios, not only validated our methods but also offered insights into the atmospheric dynamics near active fires. This study aids future research to fill observational gaps in aerosol monitoring.

We found that for ultrapure water batch leaching, the difference in specific experimental parameters, including agitation methods, filter pore size, and contact time, only led to a small and sometimes insignificant difference in determined aerosol trace element solubility. Furthermore, aerosol trace element solubility determined using four common ultrapure water leaching protocols showed good agreement.

An uncrewed aerial observing system has been developed for the measurement of vertical profiles of aerosol and cloud properties that affect Earth's radiation balance. The system was successfully deployed from a ship and from a coastal site and flown autonomously up to 3050 m and for 4.5 h. These results indicate the potential of the observing system to make routine, operational flights from ships and land to characterize aerosol interactions with radiation and clouds.

This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.

Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.

Secondary aerosol is formed in the atmosphere from gaseous emissions. Oxidation flow reactors used in secondary aerosol research do not immediately respond to changes in the inlet concentration of gases because of their broad transfer functions. This may result in incorrect secondary aerosol production factors determined for vehicles. We studied the extent of possible errors and found that oxidation flow reactors with faster responses result in smaller errors.

Clouds have been identified as the largest source of uncertainty in climate modelling. We report an untethered balloon launch of a holographic imager through clouds. This is the first time a holographic imager has been deployed in this way, enabled by the light weight and low cost of the imager. This work creates the potential to significantly increase the availability of cloud microphysical measurements required for the calibration and validation of climate models and remote sensing methods.

The characterization of the urban microclimate starts with atmospheric monitoring using a dense array of sensors to capture the spatial variations induced by the different morphology, land cover, and presence of vegetation. To provide a new sensor for this scope, this paper evaluates the outdoor performance of a commercial mobile sensor. The results mark the sensor's ability to capture the same atmospheric variability as the reference, making it a valid solution for atmospheric monitoring.

Extreme wildfire events are becoming more common with climate change. The smoke plumes associated with these wildfires are not captured by current operational satellite products due to their high optical thickness. We have developed a novel aerosol retrieval for the Advanced Himawari Imager to study these plumes. We find very high values of optical thickness not observed in other operational satellite products, suggesting these plumes have been missed in previous studies.

In our study, we examined how NO₂, temperature, and relative humidity influence the calibration of PurpleAir PA-II sensors. We found that incorporating NO₂ data from collocated reliable instruments enhances PM_2.5 calibration performance. Due to the impracticality of collocating reliable NO₂ instruments with sensors, we suggest using distant NO₂ data for calibration. We demonstrated that performance improves when distant NO₂ correlates highly with collocated NO₂ measurements.

Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.