This study examines the aerosol hygroscopicity and mixing state at Huashan (2060 m), a key free tropospheric site in central China. We find that hygroscopicity depends on particle size, source-related changes, and moisture-driven processing, which distinguishes this region from other high-altitude regions and may provide key constraints for aerosol-cloud and regional climate models.

The impacts of Saharan dust aerosols on 3-D structure of organized precipitation systems of different horizontal sizes over the tropical Atlantic Ocean in spring were studied using multiple satellite observations. Results show that under comparable thermodynamic conditions, dust-laden precipitation systems have higher storm tops, broader upper-level precipitation areas with more large particles, stronger convective activities, and heavier surface rain rates than clean ones.

This study optimizes non-methane volatile organic compound (NMVOC) emissions in China using satellite formaldehyde data from Ozone Mapping and Profiler Suite (OMPS) and Tropospheric Monitoring Instrument (TROPOMI). By applying an advanced inversion system, we produced improved NMVOC emission inventories in 2019 and 2020. The optimized results improve formaldehyde and ozone simulations in general, and a consistency analysis is further designed to assess the reliability of these two posteriors.

We used satellite data and machine learning to better understand how tiny particles in the atmosphere affect clouds and their brightness. At higher spatial resolution, we discovered a new “M”-shaped pattern in the relationship between cloud water and droplet concentration unlike the inverted-V shape observed at coarsely gridded scales. Cloud water increases more with droplet concentration when rain is present. These findings support the development of next-generation atmospheric models.

We find that wind variations at the equator (QBO) modulate the occurrence of Arctic polar stratospheric clouds (PSCs), which are key contributors to ozone depletion. During westerly QBO, the PSC occurrence is significantly greater than during easterly QBO. The QBO affects PSC mainly through temperature, while H₂O and HNO₃ have less effect. This suggests that future climate change may affect ozone recovery if it alters the QBO pattern. This study provides a new perspective on ozone prediction.

We used computer simulations to show that soot from wildfires and human activities has a bigger impact on high-altitude clouds than previously known. These particles create more ice crystals, which leads to a net warming effect on the climate in polar regions. Understanding this process is crucial for making accurate climate predictions as global wildfire activity increases.

Clouds are crucial for understanding and predicting climate, yet their processes remain uncertain in global models. We reproduced detailed observations from a lidar and a wind-lidar using an advanced instrument simulator to evaluate how well the model represents clouds. A dedicated module was developed for the wind-lidar. Both instruments reveal comparable cloud biases, confirming its value for improving model evaluation and enabling consistent multi-decade assessments with more recent sensors.

Our study examined brown carbon – organic aerosols that absorb light – at the remote Tibet and urban Guangzhou. Field data showed Tibet’s brown carbon absorbs about 10 times less than Guangzhou’s, due to cleaner air. Yet, over 75 % of its light absorption still comes from primary emission, which causes over 98 % of its climate-warming effect in both places. This study advances understanding of brown carbon dynamics and its sources in diverse environments for global climate effects.

This study compares carbonaceous aerosols source apportionment at paired traffic and background locations in urban environment (Strasbourg, France). Positive matrix factorization was applied (individually and in a combined input dataset) to aerosol mass spectrometry measurements at both sites, providing notably insights into the challenges of attributing real sources to organic aerosol (OA) factors and the impact of instrumental result specificities leading to differences in OA mass spectra.

Wildfire smoke can travel far from its source, affecting air quality far from the fire itself. This study looks at how two key factors – how much smoke is emitted & how high it rises – affect how smoke spreads. Using data from a major 2008 Siberian wildfire, four models were tested. Results show that models often inject smoke too low & remove it too quickly, missing high-altitude smoke seen by satellites. Better estimates of smoke height and removal are crucial to improve air quality forecasts.

We investigate whether the 2022 Hunga eruption could affect surface climate via indirect pathways using large ensembles of Earth System Model simulations. These suggest that the eruption could have a non-negligible influence on regional surface climate, and we discuss the mechanisms via which such an influence could occur but also highlight that the forcing is relatively weak compared to natural climate variability which significantly hinders the detection of such impacts in the real world.

Mineral dust absorbs solar and terrestrial radiation, modifying the environment where clouds exist. When above low-level clouds, dust often increases cloud cover due to shortwave absorption. Using satellite data over the North Atlantic Ocean, we show that longwave absorption by dust reduces cloud-top cooling and weakens the increase in low-level cloud. Our results highlight the importance of accurately representing longwave effects of dust in model assessments of aerosol-climate interactions.

Long-term particulate matter (PM) filter sampling at a French urban background and temperature measurements at different altitudes were used to investigate decadal trends of the main PM sources and related oxidative potential metrics. Positive Matrix Factorization analyses were conducted on the corresponding 11-year dataset, which determined ten PM sources. Temporal evolution of these sources is investigated, highlighting a strong downward trend of anthropogenic sources over 11 years.

Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and using machine learning to emulate millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.

The US Department of Energy Atmospheric Radiation Measurement (ARM) North Slope of Alaska Facility has measured solar and atmospheric infrared radiation, and cloud properties, for the past 25 years. Statistically significant trends are emerging, including increasing infrared radiation due to a warming atmosphere, and decreasing solar radiation due to increasing liquid water content in clouds. These trends are influenced by large-scale atmospheric circulation patterns and by atmospheric rivers.

We studied air pollution caused by volcanic emissions, a poorly understood hazard in populated areas. We present a large dataset of high-quality measurements of sulfur dioxide gas and fine aerosol particulate matter collected during ongoing series of eruptions in Iceland. We revealed rapid, localized changes in pollutant concentrations at ground level, with implications for assessing population exposure during volcanic eruptions.

The particle chemical morphology is important to atmospheric multiphase and heterogeneous chemistry. This work directly observed the core-shell structure and water uptake behavior of individual submicron aerosol particles at an urban site and elucidated the potential impact on particle reactive uptake and heterogeneous reactions.

The chemical composition of organic particles in the Amazon rainforest was investigated to understand how biogenic and human emissions influence the atmosphere in this unique ecosystem. Seasonal patterns were found where wet seasons were dominated by biogenic compounds from natural sources while dry seasons showed increased fire-related pollutants. These findings reveal how emissions, fires and long-range transport affect atmospheric chemistry, with implications for climate models.