We developed a new Python software tool that standardises and automates the analysis of data from a cloud simulation chamber. It identifies ice-forming particles in the atmosphere and ensures consistent data quality through built-in checks, making results more comparable across studies. We also analysed measurement data to provide recommendations for improving instrument reliability and long-term monitoring of atmospheric ice-forming particles. This helps to better understand how clouds behave.

An open-access mass spectral database of identified and unidentified compounds in atmospheric and laboratory-generated organic aerosols is released to aid in future molecular discoveries in the environmental sciences.  Identification of air pollution sources and origins is improved using the ~27,000 mass spectral records in the University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES) database.

Cloud condensation nuclei are tiny particles that attract water vapor and help form clouds. A ground-based lidar method can estimate their number at different heights, but assumes the aerosol type does not change with height. Comparisons with aircraft data show good agreement of this method when aerosols are well mixed, but larger errors when stacked layers occur. We also developed an index to flag these complex conditions and indicate when this estimation method is more reliable.

We developed a Bi-clustered Recursive Bayesian Forest model that improves wind speed forecast accuracy by 48.2 % and reduces error metrics by over 60 %. The model incorporates sea-land breeze, weather stability, and atmospheric circulation indices as features, and uses bi-clustering modal classification to mitigate wind speed magnitude interactions. This machine learning-based correction technique outperforms traditional numerical models, providing more reliable wind speed forecasting.

Chilled mirror hygrometers are the most accurate instruments for measuring water vapor in the upper troposphere and lower stratosphere. The “Golden Points” and nonequilibrium correction are a new post-processing technique for these instruments, which can correct frost point data using mirror reflectance information to achieve unprecedented accuracy of better than 4 % in the H₂O mixing ratio, even under rapidly changing humidity conditions, from the ground to the middle stratosphere.

Refinement of previous work on atmospheric refractivity, providing an expression as a function of air density, temperature, and composition. Studies with radio occultations in weather prediction show that the formulation of refractivity is critical with large data volumes. Compared to earlier work, this study incorporates updated fundamental measurements, accounts for variability in atmospheric composition, and extends the model to include hydrometeors.

For the first time, real-time methane (CH₄) emissions from an open aerated sewage treatment lagoon were measured during winter and summer seasons in Australia. The study found that: 1. The emissions accounted for 25 % of CH₄ production at the aeration digestion facilities. 2. The measured CH₄ emissions were 2 times higher than estimates based on default emission factors. We recommend that urgent action is needed to mitigate CH₄ emissions at wastewater treatment plants.

N₂O is a powerful greenhouse gas mainly released from agricultural soils, but its emissions are difficult to track as they vary strongly in space and time. We tested whether combining two kind of infrared measurements in one instrument could improve ability of airborne and satellite instruments to observe these emissions. We found that this combined approach improves sensitivity to near-surface emissions with low measurement error and could guide the design of future N₂O dedicated missions.

Using three years of laser observations above Dome C, Antarctica, we examined high clouds made of liquid droplets, nitric-acid particles, and ice crystals. We found clear differences in how these clouds scatter light, while ice-rich clouds were the most variable because they are often layered or mixed. The results provide more realistic inputs for satellite checks and climate calculations, improving estimates of how polar clouds affect sunlight, heat, and ozone loss.

Weather radar data often contains significant noise that obscures storm details. Traditional cleaning methods are computationally slow because they must adjust for the complex spreading geometry of radar beams. We developed a new, highly efficient algorithm that solves this by processing data as frequencies. This method reduces hours of computer processing time to seconds and effectively removes noise without distorting features.

Between October 2022 and January 2023, the Water Vapour Lidar Network Assimilation (WaLiNeAs) campaign was conducted on the western Mediterranean by four European countries. To improve the forecasting of heavy precipitation events, eight ground-based stations equipped with water vapour Raman lidars were strategically deployed. They offered a valuable chance to verify the consistency of the water vapour products of both the Infrared Atmospheric Sounding Interferometer (IASI) and ERA5 reanalysis.

We evaluated dimethyl sulfoxide (DMSO) as a safe, non-flammable working fluid for condensation particle counters, comparing it with butanol under varied pressures, temperatures, and aerosols. Laboratory, field, and simulation results show reliable particle activation, comparable counting efficiency, reduced fluid use, and stable long-term operation. Mixtures with water extend usability, supporting safe monitoring in remote or harsh environments.

Human activity drives increases in atmospheric nitrous oxide. Stable isotopes help trace the pathways involved. We developed a reliable way to calibrate measurements of rare isotopic variants of nitrous oxide so results from different labs can be compared. By heating nitrous oxide with a catalyst, the molecules reach well-defined equilibrium patterns suitable as a reference. To measure these isotopic variants quickly and precisely, we improved a laser-based measurement approach.

Landsat 8 images map the land but must be corrected for the atmosphere. The aerosol type assumed in this step affects accuracy. To improve this, we used Landsat 8 data from one hundred sites worldwide to compare three common assumptions. The best choice depends on the situation: one for general use and for aerosol amount, another for bright surfaces like deserts, and the standard one in some bands. The results give guidance on which to use when, so land surface maps can be more accurate.

We introduce a new lidar-based measurement technique that can observe small particles in the middle atmosphere, up to 30 km altitude, both during the day and at night. The compact instrument, with a volume of about one cubic meter, provides high-accuracy vertical profiles of aerosols and can be deployed at different locations worldwide. Comparisons with satellite data show strong agreement, highlighting its potential for longterm monitoring of stratospheric aerosols.