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Centre for Atmospheric Science

Dr David Topping

Dr David Topping

Research Fellow / NCAS Scientist

Bsc Pure Physics (UMIST) 2001, PhD: Modelling the hyrgoscopic properties of aerosols (UMIST/Manchester) 2005

Room Number: 3.13 [Simon Building]
Tel: +44 (0)161 306 2490
Email: david.topping@manchester.ac.uk


Professional biography

My research interests focus on building computational models of atmospheric aerosol particles for use in interpretation of field experiments and as sub models for incorporation in climate change models.  This broad classification masks a hierarchy of models and techniques with greatly varying complexity and range of applicability. 

At the single particle level, highly detailed theoretical tools have been developed to gain further understanding on the link between the chemical nature of organic aerosol, its interaction with inorganic components, and the associated impact on aerosol and cloud properties.   Specifically, a detailed multi-component thermodynamic equilibrium model was designed to use information on aerosol size, chemical composition (pure component thermodynamic properties, organic functionality and inorganic ions) to predict the equilibrium composition at ambient conditions. The model has already been used to resolve aerosol hygroscopicity of ambient and laboratory particles using functionality derived from ensemble mixtures and known compositions from targeted studies.  The ability to include the influence of curvature has also allowed insight into our ability to resolve cloud activating potential of aerosol from targeted laboratory systems and ensemble mixtures derived from chamber simulations.  Such studies have in turn highlighted where specific gaps exist in both models and measurement techniques.  These tools have been widely used by Manchester and external university groups such as, for example, The California Institute of Technology (US), The University of Leipzig (Germany), The University of Bristol (UK) to name but a few. 

The highly complex modelling tools are also used to drive process parameterization in large scale models which demand numerical and chemical complexity be kept to a minimum.  This includes parameterization of key parameters which dictate water uptake and gas/particle partitioning. A reduced complexity thermodynamic module has been derived to predict both, which is tailored to specific organic functionality and key inorganic components. These tools are being implemented in regional and global climate models such as WRF-CHEM (US) and COSMO-ART (Germany) and have been supplied to the developers of the UK Chemistry Aerosol community model (UKCA), a joint NCAS-Met Office programme funded by NCAS, GMR and DEFRA

Specific research interests

Organic aerosol particles. Atmospheric Science. Thermodynamics