1. A Spatial-Temporal Interpretable Deep Learning Model for improving interpretability and predictive accuracy of satellite-based PM2.5. (15th March 2021) Authors: Yan, Xing; Zang, Zhou; Jiang, Yize; Shi, Wenzhong; Guo, Yushan; Li, Dan; Zhao, Chuanfeng; Husi, Letu Journal: Environmental pollution Issue: Volume 273(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Dust modeling over East Asia during the summer of 2010 using the WRF-Chem model. (July 2018) Authors: Chen, Siyu; Yuan, Tiangang; Zhang, Xiaorui; Zhang, Guolong; Feng, Taichen; Zhao, Dan; Zang, Zhou; Liao, Shujie; Ma, Xiaojun; Jiang, Nanxuan; Zhang, Jie; Yang, Fan; Lu, Hui Journal: Journal of quantitative spectroscopy & radiative transfer Issue: Volume 213(2018) Page Start: 1 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Estimations of indirect and direct anthropogenic dust emission at the global scale. (1st March 2019) Authors: Chen, Siyu; Jiang, Nanxuan; Huang, Jianping; Zang, Zhou; Guan, Xiaodan; Ma, Xiaojun; Luo, Yuan; Li, Jiming; Zhang, Xiaorui; Zhang, Yanting Journal: Atmospheric environment Issue: Volume 200(2019) Page Start: 50 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. Explainable and spatial dependence deep learning model for satellite-based O3 monitoring in China. (1st December 2022) Authors: Luo, Nana; Zang, Zhou; Yin, Chuan; Liu, Mingyuan; Jiang, Yize; Zuo, Chen; Zhao, Wenji; Shi, Wenzhong; Yan, Xing Journal: Atmospheric environment Issue: Volume 290(2022) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. New global aerosol fine-mode fraction data over land derived from MODIS satellite retrievals. (1st May 2021) Authors: Yan, Xing; Zang, Zhou; Liang, Chen; Luo, Nana; Ren, Rongmin; Cribb, Maureen; Li, Zhanqing Journal: Environmental pollution Issue: Volume 276(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. New interpretable deep learning model to monitor real-time PM2.5 concentrations from satellite data. (November 2020) Authors: Yan, Xing; Zang, Zhou; Luo, Nana; Jiang, Yize; Li, Zhanqing Journal: Environment international Issue: Volume 144(2020) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. Quantifying contributions of natural and anthropogenic dust emission from different climatic regions. (October 2018) Authors: Chen, Siyu; Jiang, Nanxuan; Huang, Jianping; Xu, Xiaoguang; Zhang, Huiwei; Zang, Zhou; Huang, Kangning; Xu, Xiaocong; Wei, Yun; Guan, Xiaodan; Zhang, Xiaorui; Luo, Yuan; Hu, Zhiyuan; Feng, Taichen Journal: Atmospheric environment Issue: Volume 191(2018) Page Start: 94 Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval. (1st March 2020) Authors: Yan, Xing; Luo, Nana; Liang, Chen; Zang, Zhou; Zhao, Wenji; Shi, Wenzhong Journal: Atmospheric environment Issue: Volume 224(2020) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Understanding global changes in fine-mode aerosols during 2008–2017 using statistical methods and deep learning approach. (April 2021) Authors: Yan, Xing; Zang, Zhou; Zhao, Chuanfeng; Husi, Letu Journal: Environment international Issue: Volume 149(2021) Page Start: Record Type: Journal Article View Content: Available online (eLD content is only available in our Reading Rooms) ↗