Congbo Song

Dr. Congbo Song is a Senior Research Scientist in Data Science and Analytics for Atmospheric Air Pollution at the National Centre for Atmospheric Science (NCAS) within the University of Manchester's Department of Earth and Environmental Science. He specializes in source emissions, source apportionment, air pollution, and machine learning applications in environmental science. His work focuses on understanding the impacts of emissions from vehicles, coal combustion, and biomass burning on air quality and human health. He has coordinated large field campaigns in the UK and China, including Arctic research cruises, and contributed to major projects like SEANA and COP-AQ.

• Education: Doctor of Engineering (Nankai University, 2019), Master of Engineering (Nankai University, 2015), Bachelor of Engineering (Beijing University of Science & Technology, 2012)
• Research Interests: Real-time source apportionment using single-particle mass spectrometry, causal inference for air quality management, and data-driven models for net-zero emissions.

He has authored/co-authored over 40 peer-reviewed papers with 2,800+ citations and an H-index of 21. His work contributes to UN Sustainable Development Goals related to climate action and clean energy. He is part of the Manchester Environmental Data Analytics Lab (MEDAL), collaborating on advanced instrumentation and multivariate data analysis techniques.