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Song Liu
Research Assistant Professor

Basic Introduction:

Song Liu obtained her PhD in atmospheric remote sensing from Technical University of Munich and worked at German Aerospace Center before joining SUSTECH. Her works mainly focus on satellite remote sensing retrieval and chemical model simulation of atmospheric trace gases. She has participated in a series of satellite remote sensing projects in the European Union and published more than 20 peer-review journal articles.


Professional Experience:

2023 - Present: Research Assistant Professor at Southern University of Science and Technology

2021 - 2023: Postdoctoral Researcher at Southern University of Science and Technology

2020 - 2021: Postdoctoral Researcher at German Aerospace Center



2015-2019: PhD at Technical University of Munich

2012-2015: MSc at Technical University of Munich

2011-2015: MSc at Wuhan University

2007-2011: BEng at Wuhan University


Selected funded projects:

1. Driving Mechanism of Chinese NOx Emission Evolution Based on Long-Term Satellite Remote Sensing

2. Monitoring of Glyoxal Emission in the Greater Bay Area using Geostationary Satellite GEMS


Research Interests:

3. Satellite Remote Sensing Monitoring of Trace Gases

4. Atmospheric Chemical Modeling and Emission Inversion


Published Works:

1. Song Liu, Lei Zhu, Pieter Valks, Gabriele Curci, Yuyang Chen, Lei Shu, Shuai Sun, Dongchuan Pu, Xicheng Li, Juan Li, Xiaoxing Zuo, Weitao Fu, Yali Li, Peng Zhang, Xin Yang, and Tzung-May Fu: Satellite NO2 retrieval complicated by aerosol composition over global urban agglomerations: seasonal variations and long-term trends (2001-2018), Environ. Sci. Technol. 2024.

2. Song Liu#, Lei Shu#, Lei Zhu, Yu Song, Wenfu Sun, Yuyang Chen, Dakang Wang, Dongchuan Pu, Xicheng Li, Shuai Sun, Juan Li, Xiaoxing Zuo, Weitao Fu, Xin Yang, and Tzung-May Fu: Underappreciated Emission Spikes From Power Plants During Heatwaves Observed From Space: Case Studies in India and China, Earth's Future 2024.

3. Song Liu, Xicheng Li, Juan Li, Lei Shu, Tzung-May Fu, Xin Yang, and Lei Zhu: Observing network effect of shipping emissions from space: A natural experiment in the world’s busiest port, Proc. Natl. Acad. Sci. Nexus 2023.

4. Yuyang Chen, Song Liu*, Lei Zhu*, Sora Seo, Andreas Richter, Xicheng Li, Ao Ding, Wenfu Sun, Lei Shu, Xuan Wang, Pieter Valks, Francois Hendrick, Theodore K. Koenig, Rainer Volkamer, Bin Bai, Dakang Wang, Dongchuan Pu, Shuai Sun, Juan Li, Xiaoxing Zuo, Weitao Fu, Xin Yang, and Tzung-May Fu: Global observations of tropospheric bromine monoxide (BrO) columns from TROPOMI, J. Geophys. Res. Atmos. 2023.

5. Jing Wei#, Song Liu#, Zhanqing Li, Cheng Liu, Kai Qin, Xiong Liu, Rachel T. Pinker, Russell R. Dickerson, Jintai Lin, K. F. Boersma, Lin Sun, Runze Li, Wenhao Xue, Yuanzheng Cui, Chengxin Zhang, and Jun Wang: Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence, Environ. Sci. Technol. 2022.

6. Song Liu*, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, Steffen Beirle, Ehsan Khorsandi, Frank Baier, Vincent Huijnen, Alkiviadis Bais, Sebastian Donner, Steffen Dörner, Myrto Gratsea, François Hendrick, Dimitris Karagkiozidis, Kezia Lange, Ankie J. M. Piters, Julia Remmers, Andreas Richter, Michel Van Roozendael, Thomas Wagner, Mark Wenig, and Diego G. Loyola: An improved TROPOMI tropospheric NO2 research product over Europe, Atmos. Meas. Tech. 2021.

7. Song Liu*, Pieter Valks, Steffen Beirle, and Diego G. Loyola: Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic, Air Qual. Atmos. Health 2021.

8. Song Liu*, Pieter Valks, Gaia Pinardi, Jian Xu, Athina Argyrouli, Ronny Lutz, L. Gijsbert Tilstra, Vincent Huijnen, François Hendrick, and Michel Van Roozendael: An improved air mass factor calculation for NO2 measurements from GOME-2, Atmos. Meas. Tech. 2020.

9. Song Liu*, Pieter Valks, Gaia Pinardi, Isabelle De Smedt, Huan Yu, Steffen Beirle, and Andreas Richter: An improved total and tropospheric NO2 column retrieval for GOME-2, Atmos. Meas. Tech. 2019.