Improvement of composition and property prediction techniques for for Secondary Organic Aerosol (SOA)

Aerosol particles remain highly uncertain contributors to climate change, influencing climate directly by the scattering and absorption of solar radiation and indirectly through their role as cloud condensation nuclei. Atmospheric loading of particulate matter also has serious implications for urban air quality. Historically, it was assumed that aerosol particles were composed only of inorganic material. However, it has been found that organic components may constitute a substantial fraction of the aerosol composition, ranging from 20-60% of the fine particulate matter depending on the location. Condensed organic material is either directly emitted (primary) or formed in-situ by condensation and transformation of low-volatility and semi-volatile products derived from photo-oxidation of anthropogenic and biogenic volatile organic compounds (secondary organic aerosol:SOA). Gas-to-aerosol partitioning, or creation of SOA, is key to determining the chemical composition and loading of aerosol particles. A detailed knowledge of the formation, properties and transformation of SOA is therefore required to evaluate its impact on atmospheric processes, climate and human health. However, organic material can comprise many thousands, as yet largely unidentified, compounds with a vast range of properties. As a consequence, the chemical and physical processes associated with secondary organic aerosol (SOA) formation are complex and varied, and a quantitative and predictive understanding of SOA formation does not exist and therefore represents a major research challenge in atmospheric science!

Key uncertainties associated with our understanding of SOA formation have been identified. A compound will partition to the particulate phase if its equilibrium vapour pressure is low enough. This is dependent on the pure component vapour pressure, which can further decrease if the compound undergoes condensed phase reactions in the aerosol phase, enhancing gas/particle partitioning. Unfortunately, uncertainties associated with pure component vapour pressures and effective volatility of mixtures are enough to cause uncertainties in aerosol mass spanning up to 4 orders of magnitude. Vapour pressure predictive techniques are largely based on atmospherically irrelevant compounds used within industrial engineering and there is a large gap concerning the rates and importance of postulated relevant condensed phase reactions which we cannot even elucidate on using current analytical laboratory techniques.

In this proposal we aim to address these fundamental uncertainties via

1) Measurement of pure component vapour pressures using our well-established and validated method of Knudsen Effusion Mass Spectrometry. The resulting data will be assimilated into the Dortmund Databank (DDB) and new model revisions will be carried out by our industrial partner.

2) Directly link chemical composition to volatility within mixtures for the first time

3) Assess the complexity required to truly capture the SOA formation in atmospheric models.

The primary non-academic end-users of the proposed programme output in the UK would be the Met Office via existing links between the PI and the UKCA Climate- Chemistry-Community-Aerosol model, a joint NCAS-Met Office programme funded by NCAS, GMR and DEFRA.The impacts of aerosol on climate are still credited with the largest uncertainty in climate forcing and a large part of the radiatively active boundary layer sub-micron aerosol burden is organic. Prior to the proposed work, accurate model descriptions of aerosol formation are unavailable & our study of those properties dictating gas/particle partitioning of organic compounds will be inform such a climate-focused goal. Other international non-academic agencies conducting IPCC simulations would be best placed to use the same reduced complexity SOA formalisms as supplied to the Met Office. Other specific non-academic end users includes the Dortmund Databank Consortium (DDB), who will benefit from a study of compounds not covered in their existing databases and predictive software (see letter of support - DDB) and the British Aerosol Manufacturers Association (see letter of support - BAMA). This scarcity of data causes empirically constrained predictive models to remain inaccurate and unevaluated when applied to atmospheric systems. The DDB is the largest data bank for experimental data on pure components and mixtures and available via distributed software, online (e.g. www.stn- international.de) and in printed form. Customers of DDB include about 50 chemical and engineering companies throughout the world as well as university and research institutions.

A number of academic communities are identified as having an interest in this work, ranging from atmospheric scientists through to physicists. The atmospheric community will benefit from provision of a comprehensive set of fundamental property measurements, development of novel instrumentation and improved predictive models. Dissemination of knowledge through distributed software, printed reference material via collaboration with industrial partners, and online tools developed in this project will vastly increase our ability to benefit researchers in other fields indirectly. We will disseminate results from this work through presentations at conferences in the UK and abroad, through research papers in high profile journals, through our network of collaborators and associates, and the online tools developed in this project (discussed shortly) .

At UoM we will use a Science Communicator in residence, Katherine Harrison to help us to distil the results from this work into a variety of documents that can be used by lay people at various levels of science literacy. A considerable effort will be directed to schools and teachers, where a public lecture will be developed to present the main results to schools and the general public, many times over the course of the 3 years of this project. We will also have a significant presence at UK Science Festivals, where we will present talks at a suitable level. We will also, in collaboration with Harrison, a former school teacher, write articles for schools and teachers and develop resource packs for this group. Furthermore, we will continue to work closely with the University media centres to ensure that all good news stories are broadcast effectively.

It is crucial that tools are developed to ensure benefits for a wide-range of end-users becomes sustainable beyond the duration of the project. To this end, a novel data portal will be constructed and hosted at UoM that provides access to continually updated peer reviewed data derived from this program, a blog, introductory material (see above) and maintains consistent in-house data stewardship and continual support. The incorporation of modeling tools improved in this project within an informatics suite, developed under a separate NERC grant, linked to this portal will be tailored to provide a useful online teaching resource.