High-precision 3D Modeling of Construction Waste Pile Bodies by Integrating Multi-source Data

This study developed a new satellite-based global land daily FMF dataset (Phy-DL FMF) by synergizing the advantages of physical and deep learning methods at a 1° spatial resolution by covering the period from 2001 to 2020. The Phy-DL FMF was extensively evaluated against ground-truth AERONET data and tested on a global scale against conventional satellite-based FMF products to demonstrate its superiority in accuracy.

New particle formation (NPF) can be a large source of CCN and affect weather and climate. Here we show that the NPF contributes largely to cloud droplet number concentration (N_d) but is suppressed at high particle number concentrations in Beijing due to water vapor competition. We also reveal a considerable impact of primary sources on the evaluation in the urban atmosphere. Our study has great significance for assessing NPF-associated effects on climate in polluted regions.

Using long-term multi-source data, this study shows significant impacts of fire events on aerosol properties over Australia. The contribution of carbonaceous aerosols to the total was 26 % of the annual average but larger (30–43 %) in September–December; smoke and dust are the two dominant aerosol types at different heights in southeastern Australia for the 2019 fire case. These findings are helpful for understanding aerosol climate effects and improving climate modeling in Australia in future.

The hygroscopic growth function of aerosol particles is derived from Raman lidar, whose dependence on aerosol chemical composition is investigated using data from an aerosol chemical speciation monitor (ACSM) and a hygroscopic tandem differential mobility analyzer (H-TDMA) deployed in China. Two distinct cases were chosen with marked differences in their hygroscopic growth, which was fitted by the Kasten model. The differences were attributed to different amounts of chemical species.