Publications by authors named "G de Leeuw"
New Particle Formation (NPF) is an important process of secondary aerosol production in the atmosphere, which has significant impacts on the Earth's radiation balance, air quality, and climate change. In this study, we develop a method to identify NPF events based on ground-based remote sensing. We propose a proxy to characterize NPF events utilizing ground-based remote sensing of gaseous precursors and aerosol optical depth (AOD).
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- Two major super dust storms in March 2021 struck Mongolia and Northern China, resulting in significant fatalities and economic losses.
- Accurate forecasting of these storms is crucial, and soil moisture levels play a key role, although they can vary significantly in desert regions.
- Model experiments revealed that different soil moisture datasets greatly affect dust emission estimations, with the ERA5 dataset providing the best simulation, highlighting the Mongolian Gobi Desert as the primary dust source contributing to pollution in neighboring regions.
A two-stage model integrating a spatiotemporal linear mixed effect (STLME) and a geographic weight regression (GWR) model is proposed to improve the meteorological variables-based aerosol optical depth (AOD) retrieval method (Elterman retrieval model-ERM). The proposed model is referred to as the STG-ERM model. The STG-ERM model is applied over the Beijing-Tianjin-Hebei (BTH) region in China for the years 2019 and 2020.
View Article and Find Full Text PDFFine particulate matter, with an aerodynamic diameter ≤ 2.5 μm (PM), is a severe problem in China. The lack of ground-based measurements and its sparse distribution obstruct long-term air pollution impact studies over China.
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