Imperial College London

Dr Marc Stettler

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Reader in Transport and the Environment



+44 (0)20 7594 2094m.stettler Website




614Skempton BuildingSouth Kensington Campus





Dr Marc Stettler is Reader in Transport and the Environment in the Department of Civil and Environmental Engineering at Imperial College London. He leads the Transport & Environment Laboratory and the Network of Excellence in Aerosols and Health. He is the Director of Undergraduate Studies in the Department of Civil and Environmental Engineering for the MEng in Civil Engineering.

Marc's research focuses on evaluating and reducing the effect of transport activity on climate change and air pollution, with particular attention to understanding sources of greenhouse gases (GHGs) and pollutant emissions, especially nanoparticles. He leads research projects spanning across transport modes from road to aviation. He works on improving understanding of emissions sources and their impact on air pollution and health; aerosol science and characterisation; sustainable aviation; and lifecycle analyses of alternative fuels and vehicle technologies.

Marc is currently the General Secretary of the UK and Ireland Aerosol Society. He is also a member of the Greener by Design Committee at the Royal Aeronautical Society. He contributed to the UK Government Office for Science Future of Mobility project and he chairs the Scientific Advisory Committee of the AIR, which aims to make vehicle emissions data more transparent. He is a member of the NERC funded network to Tackle Air Pollution in Schools (TAPAS).

Marc is the Imperial lead for the EPSRC funded Centre for Doctoral Training in Aerosol Science, which brings together seven UK universities and industrial and public-sector partners in the areas of healthcare, material science, energy and transport, environment, consumer products and agrochemicals.

Marc joined Imperial as a Lecturer in 2015. Prior to that, he completed his PhD on the impacts of aviation emissions at the University of Cambridge in 2013. He has an MPhil in Engineering for Sustainable Development from Cambridge, and a BSc in Natural Sciences from the University of Durham. He was awarded the President's Award for Outstanding Early Career Researcher at Imperial College London in 2018, and the Outstanding PhD Dissertation prize from the Department of Engineering, University of Cambridge in 2014.

More information on his research group is available at the Transport & Environment Laboratory website.


Opportunities and openings in my group are generally posted on my Twitter page @MarcEJStettler.

PhD project opportunities in the Centre for Doctoral Training in Aerosol Science will be posted on the central CDT website. These will typically be advertised in early November with assessment taking place in late January. 

Videos & Media

Research on mitigating aviation contrails
Wired | CNN | Scientific American | The Naked Scientists | BBC | New Scientist | The Guardian

Exposure to pollution in cars
Sky News, June 2019

Reaching melting point - the importance of 1.5°C
Advanced Propulsion Centre Future of Technology Series, November 2018

Tracking automobile emissions in real time 
World Economic Forum, September 2018



Teoh R, Engberg Z, Shapiro M, et al., 2024, The high-resolution Global Aviation emissions Inventory based on ADS-B (GAIA) for 2019–2021, Atmospheric Chemistry and Physics, Vol:24, Pages:725-744

Jagtap SS, Childs PRN, Stettler MEJ, 2024, Performance sensitivity of subsonic liquid hydrogen long-range tube-wing aircraft to technology developments, International Journal of Hydrogen Energy, Vol:50, ISSN:0360-3199, Pages:820-833

Wang Z, Acha S, Bird M, et al., 2024, A total cost of ownership analysis of zero emission powertrain solutions for the heavy goods vehicle sector, Journal of Cleaner Production, Vol:434, ISSN:0959-6526

Mehlig D, Staffell I, Stettler M, et al., 2023, Accelerating electric vehicle uptake favours greenhouse gas over air pollutant emissions, Transportation Research Part D: Transport and Environment, Vol:124, ISSN:1361-9209

Kuo C-F, Tsai C-Y, Cheng W-H, et al., 2023, Machine learning approaches for predicting sleep arousal response based on heart rate variability, oxygen saturation, and body profiles., Digit Health, Vol:9, ISSN:2055-2076

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