Simulating and Simplifying the Physicochemical Complexity of Gas-Aerosol Systems to Promote Development of the Next Generation of Atmospheric 3-D Models

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Aerosol particles are important constituents of the atmosphere affecting clouds, air quality and Earth's climate. The amounts and distribution of these tiny particles in the surface layers of the atmosphere are important indicators of air quality, often reported in terms of particulate matter mass concentrations (PM10, PM2.5) alongside with ozone and nitrous oxide concentrations. Fine and ultrafine particles can easily enter the lungs and may affect adversely the health of humans. Aerosol particles play a crucial role in the formation of clouds and influence the microphysical properties of liquid water and ice clouds. The recent, comprehensive fifth assessment report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) highlights that aerosols remain poorly constrained climate agents of considerable importance: “There is high confidence that aerosols and their interactions with clouds have offset a substantial portion of global mean forcing from well-mixed greenhouse gases. They continue to contribute the largest uncertainty to the total radiative forcing (RF) estimate.” Observed levels of aerosols globally show that organic compounds typically contribute 30% to 80% of the aerosol mass in the troposphere. The major part of this organic aerosol fraction is so-called secondary organic aerosol (SOA) formed from the oxidation of volatile organic compounds and subsequent gas-particle partitioning. It is of central importance for actions targeting the improvement of urban and regional air quality, as well as the critical assessment of climate sensitivity, to understand how chemical reactions and partitioning of volatile organic and inorganic species influences mass concentrations, chemical composition, and size distribution of atmospheric aerosols. Current atmospheric 3-D models implement such physicochemical processes by means of highly simplified schemes only. Most of the 3-D models substantially underpredict observed aerosol levels, constituting one of the main uncertainties in current assessments of air quality and global climate. It is a long-term goal of our research program to develop and utilize methods to translate process-level knowledge from laboratory aerosol experiments, field studies, theory, and box models into practical and justified process parameterizations for use in 3-D chemical transport and chemistry-climate models. Accordingly, our short-term objectives for the next five years include the development of a novel physicochemical modeling framework enabling simplified simulations of aerosol formation and chemical evolution and the evaluation and design of smog chamber experiments. The fundamental insights gained from a box model comprising key physicochemical processes of organic aerosol formation and chemical aging will provide a sound basis from which to assess the feasibility of different levels of simplifications, such as the number and classes of organic surrogate compounds required for process parameterizations in 3-D models. The influence of relative humidity on gas-particle partitioning is one of several questions we propose to study for a wide variety of secondary organic aerosol types. Model simulations in turn will allow us to establish a series of constraints and recommendations for the development of simplified yet improved parameterizations for applications in 3-D models, which largely depend on computationally efficient schemes. New parameterizations will be implemented and tested in an atmospheric chemical transport model. The proposed research offers excellent opportunities for the training of graduate students at McGill University. Our research and training efforts will be supported by mutually beneficial scientific collaborations with leading research groups from Europe and North America.