The Aralkum is a new desert in Central Asia formed by the desiccation of the Aral Sea. This has created a source of atmospheric dust, with implications for the balance of solar and thermal radiation. Simulating these effects using a dust transport model, we find that Aralkum dust adds radiative cooling effects to the surface and atmosphere on average but also adds heating events. Increases in surface pressure due to Aralkum dust strengthen the Siberian High and weaken the summer Asian heat low.

In the Aburrá Valley, northern South America, local emissions determine air quality conditions. However, we found that external sources, such as regional fires, Saharan dust, and volcanic emissions, increase particulate concentrations and worsen chemical composition by introducing elements like heavy metals. Dry winds and source variability contribute to seasonal influences on these events. This study assesses the air quality risks posed by such events, which can affect broad regions worldwide.

This study establishes an inventory of anthropogenic chlorine emissions in China in 2019 with expanded species (HCl, Cl^-, Cl₂, HOCl) and sources (41 specific sources). The inventory is validated by a modeling study against the observations. This study enhances the understanding of anthropogenic chlorine emissions in the atmosphere, identifies key sources, and provides scientific support for pollution control and climate change.

Methane in the atmosphere contributes to the production of ozone gas – an air pollutant and greenhouse gas. Our results highlight that simultaneous reductions in methane emissions help avoid offsetting the air pollution benefits already achieved by the already-approved precursor emission reductions by 2050 in the European Monitoring and Evaluation Programme region, while also playing an important role in bringing air pollution further down towards World Health Organization guideline limits.

Ambient fine particulate matter (PM_2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM_2.5–AOD relationship (η), can provide global PM_2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.