Aerosol mixing state significantly affects concentrations of cloud condensation nuclei (CCN), wet removal rates, thermodynamic properties, heterogeneous chemistry, and aerosol optical properties, with implications for human health and climate. Over the last two decades, significant research effort has gone into finding computationally-efficient methods for representing the most important aspects of aerosol mixing state in air pollution, weather prediction, and climate models. In this review, we summarize the interactions between mixing-state and aerosol hygroscopicity, optical properties, equilibrium thermodynamics and heterogeneous chemistry. We focus on the effects of simplified assumptions of aerosol mixing state on CCN concentrations, wet deposition, and aerosol absorption. We also summarize previous approaches for representing aerosol mixing state in atmospheric models, and we make recommendations regarding the representation of aerosol mixing state in future modelling studies.

Wildfire frequency has increased in past four decades in Canada and is expected to increase in future as a result of climate change (Wotton et al., 2010). Mercury (Hg) emissions from biomass burning are known to be significant; however, the impact of biomass burning on air concentration and deposition fluxes in Canada has not been previously quantified. We use estimates of burned biomass from FINN (Fire INventory from NCAR) and vegetation-specific emission factors (EFs) of mercury to investigate the spatiotemporal variability of Hg emissions in Canada. We use Environment and Climate Change Canada's GEM-MACH-Hg (Global Environmental Multi-scale, Modelling Air quality and Chemistry model, mercury version) to quantify the impact of biomass burning in Canada on spatiotemporal variability of air concentrations and deposition fluxes of mercury in Canada. We use North American gaseous elemental mercury (GEM) observations (2010–2015), GEM-MACH-Hg, and an inversion technique to optimize the EFs for GEM for five vegetation types represented in North American fires to constrain the biomass burning impacts of mercury. The inversion results suggest that EFs representing more vegetation types – specifically peatland – are required. This is currently limited by the sparseness of measurements of Hg from biomass burning plumes. More measurements of Hg concentration in the air, specifically downwind of fires, would improve the inversions. We use three biomass burning Hg emissions scenarios in Canada to conduct three sets of model simulations for 2010–2015: two scenarios where Hg is emitted only as GEM using literature or optimized EFs and a third scenario where Hg is emitted as GEM using literature EFs and particle bound mercury (PBM) emitted using the average GEM∕PBM ratio from lab measurements. The three biomass burning emission scenarios represent a range of possible values for the impacts of Hg emissions from biomass burning in Canada on Hg concentration and deposition.We find total biomass burning Hg emissions to be highly variable from year to year and estimate average 2010–2015 total atmospheric biomass burning emissions of Hg in Canada to be between 6 and 14 t during the biomass burning season (i.e. from May to September), which is 3–7 times the mercury emission from anthropogenic sources in Canada for this period. On average, 65 % of the emissions occur in the provinces west of Ontario. We find that while emissions from biomass burning have a small impact on surface air concentrations of GEM averaged over individual provinces/territories, the impact at individual sites can be as high as 95 % during burning events. We estimate average annual mercury deposition from biomass burning in Canada to be between 0.3 and 2.8 t, compared to 0.14 t of mercury deposition from anthropogenic sources during the biomass burning season in Canada. Compared to the biomass burning emissions, the relative impact of fires on mercury deposition is shifted eastward, with on average 54 % percent of the deposition occurring in provinces west of Ontario. While the relative contribution of Canadian biomass burning to the total mercury deposition over each province/territory is no more than 9 % between 2010 and 2015, the local contribution in some locations (including areas downwind of biomass burning) can be as high as 80 % (e.g. northwest of Great Slave Lake in 2014) from May to September. We find that northern Alberta and Saskatchewan, central British Columbia, and the area around Great Slave Lake in the Northwest Territories are at greater risk of mercury contamination from biomass burning. GEM is considered to be the dominant mercury species emitted from biomass burning; however, there remains an uncertainty in the speciation of mercury released from biomass burning. We find that the impact of biomass burning emissions on mercury deposition is significantly affected by the uncertainty in speciation of emitted mercury because PBM is more readily deposited closer to the emission sources than GEM; an addition of ∼ 18 % percent of mercury emission from biomass burning in the form of PBM in the model increases the 6-year average deposition by ∼ 4 times.

A useful aerosol model must be able to adequately resolve the chemical complexity and phase state of the wide particle size range arising from the many different secondary aerosol growth processes to assess their environmental and health impacts. Over the past two decades, significant advances in understanding of gas-aerosol partitioning have occurred, particularly with respect to the role of organic compounds, yet aerosol representations have changed little in air quality and climate models since the late 1990s and early 2000s. The gas-aerosol partitioning models which are still commonly used in air quality models are separate inorganics-only thermodynamics and secondary organic aerosol (SOA) formation based on absorptive partitioning theory with an assumption of well-mixed liquid-like particles that continuously maintain equilibrium with the gas phase. These widely used approaches in air quality models for secondary aerosol composition and growth based on separated inorganic and organic processes are inadequate. This review summarizes some of the important developments during the past two decades in understanding of gas aerosol mass transfer processes. Substantial increases in computer performance in the last decade justify increasing the process detail in aerosol models. Organics play a central role during post-nucleation growth into the accumulation mode and change the hygroscopic properties of sulfate aerosol. At present, combined inorganic-organic aerosol thermodynamics models are too computationally expensive to be used online in 3-D simulations without high levels of aggregation of organics into a small number of functional surrogates. However, there has been progress in simplified modeling of liquid-liquid phase separation (LLPS) and distinct chemical regimes within organic-rich and inorganic-rich phases. Additional limitations of commonly used thermodynamics models are related to lack of surface tension data for various aerosol compositions in the small size limit, and lack of a comprehensive representation of surface interaction terms such as disjoining pressure in the Gibbs free energy which become significant in the small size limit and which affect both chemical composition and particle growth. As a result, there are significant errors in modeling of hygroscopic growth and phase transitions for particles in the nucleation and Aitken modes. There is also increasing evidence of reduced bulk diffusivity in viscous organic particles and, therefore, traditional secondary organic aerosol models, which are typically based on the assumption of instantaneous equilibrium gas-particle partitioning and neglect the kinetic effects, are no longer tenable.

Oil sands upgrading facilities in the Athabasca oil sands region (AOSR) in Alberta, Canada, have been reporting mercury (Hg) emissions to public government databases (National Pollutant Release Inventory (NPRI)) since the year 2000, yet the relative contribution of these emissions to ambient Hg deposition remains unknown. The impact of oil sands emissions (OSE) on Hg levels in and around the AOSR, relative to contributions from global (anthropogenic, geogenic and legacy) emissions and regional biomass burning emissions (BBE), was assessed using a global 3D-process-based Hg model, GEM-MACH-Hg, from 2012 to 2015. In addition, the relative importance of year-to-year changes in Hg emissions from the above sources and meteorological conditions to inter-annual variations in Hg deposition was examined. Surface air concentrations of Hg species and annual snowpack Hg loadings simulated by the model were found comparable to measured levels in the AOSR, suggesting consistency between reported Hg emissions from oil sands activities and Hg levels in the region. As a result of global-scale transport and the long lifetime of gaseous elemental Hg (Hg(0)), surface air concentrations of Hg(0) in the AOSR reflected the background Hg(0) levels in Canada. By comparison, average air concentrations of total oxidized Hg (efficiently deposited Hg species) in the AOSR were elevated up to 60 % within 50 km of the oil sands Hg emission sources. Hg emissions from wildfire events led to episodes of high ambient Hg(0) concentrations and deposition enrichments in northern Alberta, including the AOSR, during the burning season. Hg deposition fluxes in the AOSR were within the range of the deposition fluxes measured for the entire province of Alberta. On a broad spatial scale, contribution from imported Hg from global sources dominated the annual background Hg deposition in the AOSR, with present-day global anthropogenic emissions contributing to 40 % (< 1 % from Canada excluding OSE) and geogenic and legacy emissions contributing to 60 % of the background Hg deposition. In contrast, oil sands Hg emissions were responsible for significant enhancements in Hg deposition in the immediate vicinity of oil sands Hg emission sources, which were ∼ 10 times larger in winter than summer (250 %–350 % in winter and ∼ 35 % in summer within 10 km of OSE, 2012–2013). The spatial extent of the influence of oil sands emissions on Hg deposition was also greater in winter relative to summer (∼ 100 km vs. 30 km from Hg-emitting facilities). In addition, inter-annual changes in meteorological conditions and oil sands emissions also led to significantly higher inter-annual variations in wintertime Hg deposition compared to summer. In 2015, within 10 km of major oil sands sources, relative to 2012, Hg deposition declined by 46 % in winter but 22 % annually, due to a larger OSE-led reduction in wintertime deposition. Inter-annual variations in meteorological conditions were found to both exacerbate and diminish the impacts of OSE on Hg deposition in the AOSR, which can confound the interpretation of trends in short-term environmental Hg monitoring data. Hg runoff in spring flood, comprising the majority of annual Hg runoff, is mainly derived from seasonal snowpack Hg loadings and mobilization of Hg deposited in surface soils, both of which are sensitive to Hg emissions from oil sands developments in the proximity of sources. Model results suggest that sustained efforts to reduce anthropogenic Hg emissions from both global and oil sands sources are required to reduce Hg deposition in the AOSR.

The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach for solving advection and is commonly used in numerical weather prediction (NWP) models. It has a significant impact on the accuracy of the solution and can potentially be the most expensive part of model integration. The sweep algorithm, which was first described by Mortezazadeh and Wang (2017), performs SL interpolation with the same computational cost as a third-order polynomial scheme but at the accuracy of the fourth order. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps. In this paper, we present a new application of the sweep algorithm within the context of global forecasts produced with Environment Climate Change Canada's Global Environmental Multiscale (GEM) model. Results show that the SL scheme with sweep interpolation is computationally more efficient compared to a conventional SL scheme with fourth-order polynomial interpolation, especially when a very large number of passive tracers are advected. An additional advantage of this new approach is that its implementation in a chemical and weather forecast model requires minimum modifications of the interpolation weighting coefficients. An analysis of the computational performance for a set of theoretical benchmarks as well as a global ozone forecast experiment show that up to 15 % reduction in total wall clock time is achieved. Forecasting experiments using the global version of the GEM model and the new interpolation show that the sweep interpolation can perform very well in predicting ozone distribution, especially in the tropopause region, where transport processes play a significant role.

The Multi-Compartment Hg (mercury) Modeling and Analysis Project (MCHgMAP) is an international multi-model research initiative intended to simulate and analyze the geospatial distributions and temporal trends of environmental Hg to inform the effectiveness evaluations of two multilateral environmental agreements (MEAs): the Minamata Convention on Mercury (MC) and Convention on Long-Range Transboundary Air Pollution (LRTAP). This MCHgMAP overview paper presents its science objectives, background and rationale, experimental design (multi-model ensemble (MME) architecture, inputs and evaluation data, simulations and reporting framework), and methodologies for the evaluation and analysis of simulated environmental Hg levels. The primary goals of the project are to facilitate detection and attribution of recent (observed) and future (projected) spatial patterns and temporal trends of global environmental Hg levels, and identification of key knowledge gaps in Hg science and modeling to improve future effectiveness evaluation cycles of the MEAs. The current advances and challenges of Hg models, emission inventories, and observational data are examined, and an optimized multi-model experimental design is introduced for addressing the key policy questions of the MEAs. A common set of emissions, environmental conditions, and observation datasets are proposed (where possible) to enhance the MME comparability. A novel harmonized simulation approach between atmospheric, land, oceanic and multi-media models is developed to account for the short- and long-term changes in secondary Hg exchanges and to achieve mechanistic consistency of Hg levels across environmental matrices. A comprehensive set of model experiments is developed and prioritized to ensure a systematic analysis and participation of a variety of models from the scientific community.