Microplastics are environmental contaminants of global concern. In this study, we developed a method for measuring the amount of microplastics in atmospheric samples. In doing so, we introduced a new way to collect rain/snow samples and a custom software that helps with the analysis of microplastics. We then assessed the precision of our method and tested it on real samples. Our work may be useful for researchers seeking to measure microplastics in environmental samples.

We statistically analyze the hygroscopic growth characteristics of urban anthropogenic aerosols over Wuhan, a megacity over central China, using lidar observations and Hänel parameterization from 2010 to 2024. Aerosol hygroscopic parameter γ increases from 2014 to 2017 and stabilizes at high levels afterwards, aligning with the changes in NO₂-to-SO₂ concentration ratio. Moreover, no evident differences are found across seasons, as well as between the free troposphere and boundary layer.

A new processing method for lidar data obtained from rapidly changing laser pulse lengths enables measurement of atmospheric water vapor from the ground up to 6 km. The technique blends all captured data to reveal hidden water vapor structures, especially near the surface. This solution offers continuous, high-resolution insights, key for improving weather forecasts. It showcases how flexible laser technology can enhance atmospheric observation.

We have developed a new method that uses machine learning to analyse aerosols by combining different instruments measuring at different wavelengths. This method can identify the composition of these aerosols faster and more accurately. We tested it using ground-based data. Our results show that this method can help monitor air quality and better understand the impact of aerosols on the climate.

We estimate the radiative impact of high-altitude ice clouds, including potential contrails, using satellite observations and radiative transfer calculations. Focusing on six days with potential contrails over Europe, we show that these clouds cause daytime cooling and nighttime warming. Validation through various comparisons shows that our approach provides accurate estimates of contrail radiative forcing.

Extreme rainfall can cause severe damage, especially in cities. However, national meteorological institutes have difficulties to observe such events. In this study we show that rainfall observations collected by local actors, such as municipalities and even citizens, can contribute to better rainfall observations. Sweden’s official monitoring network could not capture the event under study, whereas the complementary sensors contributed to a better understanding of the magnitude of the event.

We present PrecipBE, a multi-instrument precipitation event best-estimate data product developed at the Atmospheric Radiation Measurement (ARM) User Facility, providing time series and tabular statistics of events, which could help advance model evaluation and cloud-process studies. We demonstrate PrecipBE's utilization with a brief 30-year trend analysis of ARM Southern Great Plains (SGP) site data, suggesting shorter, less intense events, but rising annual rainfall, driven by rare extremes.

The TRANSAMA ship-based campaign (April–May 2023) aboard Marion Dufresne investigated aerosols from La Réunion to Barbados using photometer and lidar. Observations revealed clean conditions over the South Atlantic, with thin transported aerosol plumes from Southern Africa. Clouds were detected in 53 % of lidar profiles with higher occurrence in the first 2 km. The results show how combined lidar and photometer measurements can improve our understanding of aerosols in marine environment.

The Montreal Protocol has led to a slow recovery in the Earth's ozone layer. To detect such changes, and to monitor the health of the ozone layer, long term global observations are needed. The OMPS Limb Profiler (LP) series of satellite sensors are designed to meet this need. We validate the latest version OMPS LP ozone profiles against other satellite and ground based measurements. We find that OMPS LP ozone is consistent with other data sources and is suitable for use in ozone trend studies.

We evaluate the new radar module of the Community Radiative Transfer Model using radar observations from multiple frequencies. Simulated reflectivities show strong sensitivity to particle size distributions and frozen hydrometeor habits. Results highlight the role of microphysical assumptions in radar forward modeling and their importance for assimilating spaceborne radar data in weather prediction models.

The Eastern Mediterranean and Middle East is a greenhouse gas emission hotspot but lacks atmospheric monitoring. Our study introduces the first Total Carbon Column Observing Network site in this region, in Cyprus, providing high-precision columnar measurement of key greenhouse gases. This new dataset enhances global climate monitoring efforts, supports the validation of satellites, will help assess regional emission trends, filling a critical observational gap in this climate-sensitive region.

Method feasibility and practicality are important considerations for quantifying methane emissions. This study adapted the flux plane mass balance method to a rapidly deployable, operationally flexible, and user-friendly, human-portable telescoping pole-based system. Controlled release test results suggest that the pole method can be applied to moderate height sources at closer downwind distances with performance similar to other widely used mobile quantification methods.

We developed a multi-stage AutoML (Automated Machine Learning) calibration framework to improve low-cost indoor PM_2.5 sensor accuracy. Using chamber tests with varied emission sources, the method corrected drift, humidity effects, and non-linear responses, raising R² above 0.9 and halving RMSE (Root Mean Square Error). The approach enables reliable, scalable indoor air quality monitoring for research and public health applications.

We advanced the Lightning Differential Space (LDS) method, which maps time and distance between lightning strokes, and demonstrated its use across three distinct meteorological regions. By comparing stroke strength and timing, our new Current Ratio approach reveals flash initiation patterns in different storm types. The method is straightforward and data-driven, enabling physical insight without model-based analysis or prior assumptions, and supports regional lightning analysis and forecasting.

We present a global climatology of Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) version 8 chlorine monoxide (ClO), retrieved from spaceborne observations between 2002 and 2012. Due to an improved retrieval setup, the high bias and poor vertical resolution of upper stratospheric ClO, which had affected the previous V5 data set, has been removed. Comparisons with ClO observations of the Microwave Limb Sounder generally show good agreement. Differences can be explained by simulations with an atmospheric chemistry model.

Fengyun radio occultation products are useful for numerical weather prediction (NWP). However, its accuracy required to be further improved from middle stratosphere above. We developed a quality control scheme and evaluate the Fengyun bending angles’ quality. The new quality control scheme are useful in rejecting outliers and products’ quality have been well understood. The results are promising in improving the performance of Fengyun data in NWP and climate applications.

We developed a simple method to identify different types of airborne particles using laser-based measurements. It can distinguish coarse dust, fine dust, and non-dust aerosols. Tests with real data from regions affected by desert dust show the method works well. This helps improve understanding of how particles are distributed in the atmosphere, which is important for air quality and climate studies.

The Aeolus satellite's lidar system had limitations in detecting certain atmospheric layers and distinguishing between aerosol and cloud types. To improve accuracy, a new dust detection product was developed. By combining data from various sources and validating it with ground-based measurements, this enhanced product performs better than the original. It helps improve dust transport models and weather predictions, making it a valuable tool for atmospheric monitoring and forecasting.

We developed algorithms to produce JAXA ATLID L2 aerosol products using ATLID L1 data. The algorithms estimate layer identifiers such as (1) aerosol or cloud layers, (2) particle optical properties at 355 nm, (3) particle type identifiers, and (4) planetary boundary layer height. We demonstrated the algorithm performance using the simulated ATLID L1 data and found the algorithm’s capability to provide valuable insights into the global distribution of aerosols and clouds.

Dense urban CO₂ monitoring is challenging due to cost and operational constraints. We developed a mid-cost sensor network for Munich, deployed on 17 rooftops. Temperature-stabilized enclosures and automated 2-point calibration ensured reliable performance, assessed by side-by-side comparison with a Picarro reference. In 1.5 years, the network collected 90 million measurements and resolved urban-rural gradients and seasonal diurnal patterns, capturing spatial CO₂ variability at city scale.