A panel of international experts was convened in Madison, Wisconsin, in 2005, as part of the 8th International Conference on Mercury as a Global Pollutant. Our charge was to address the state of science pertinent to source attribution, specifically our key question was: "For a given location, can we ascertain with confidence the relative contributions of local, regional, and global sources, and of natural versus anthropogenic emissions to mercury deposition?" The panel synthesized new research pertinent to this question published over the past decade, with emphasis on four major research topics: long-term anthropogenic change, current emission and deposition trends, chemical transformations and cycling, and modeling and uncertainty. Within each topic, the panel drew a series of conclusions, which are presented in this paper. These conclusions led us to concur that the answer to our question is a "qualified yes," with the qualification being dependent upon the level of uncertainty one is willing to accept. We agreed that the uncertainty is strongly dependent upon scale and that our question as stated is answerable with greater confidence both very near and very far from major point sources, assuming that the "global pool" is a recognizable "source." Many regions of interest from an ecosystem-exposure standpoint lie in between, where source attribution carries the greatest degree of uncertainty.

A multiscale modeling system that consists of a global chemical transport model (CTM) and a nested continental CTM was used to simulate the global atmospheric fate and transport of mercury and its deposition over the contiguous United States. The performance of the CTMs was evaluated against available data. The coefficient of determination (r2) for observed versus simulated annual mercury wet deposition fluxes over North America was 0.50 with average normalized error and bias of 25% and 11%, respectively. The CTMs were used to conduct a global source attribution for selected receptor areas. Three global emission scenarios were used that differed in their distribution of background emissions among direct natural emissions and re-emissions of natural and anthropogenic mercury. North American anthropogenic sources were calculated to contribute only from 25 to 32% to the total mercury deposition over the continental United States. At selected receptors, the contribution of North American anthropogenic emissions ranges from 9 to 81%; Asian anthropogenic emissions were calculated to contribute from 5 to 36%; natural emissions were calculated to contribute from 6 to 59%.

[1] A model that predicts secondary organic aerosol (SOA) formation based on the thermodynamic equilibrium partitioning of secondary organic oxidation products has been developed for implementation into atmospheric models. Hydrophobic secondary products are assumed to partition to an absorbing organic aerosol consisting of primary organic aerosol (POA) and other secondary hydrophobic organics according to an equilibrium partitioning coefficient calculated iteratively for each secondary compound present. The hydrophobic module is evaluated by studying the partitioning of octadecanoic acid to surrogate POA species. As expected, the amount of octadecanoic acid predicted to be present in the aerosol phase increases as the total amount of absorbing material increases or as the total amount of acid present increases. Hydrophilic secondary compounds partition to an aqueous phase via Henry's law; the fraction of each compound's mass that partitions is determined by its Henry's law constant and its acid dissociation constant(s). The available liquid water content (LWC) of the aerosol is determined iteratively between an inorganic aerosol module and the hydrophilic module, which is evaluated by studying the partitioning of glyoxalic and malic acids. While glyoxalic acid tends to remain in the gas phase, malic acid partitions strongly to the aqueous phase, with ions being the dominant form in the aqueous phase. As expected, an increase in relative humidity increases the amount of water associated with the organics (ÁLWC), and a lower aerosol pH favors molecular solutes over ionized forms. Increasing pH results in higher effective Henry's law constants for the acids, yielding higher organic aerosol concentrations. Results also indicate that increasing ÁLWC induces additional partitioning of inorganics to the aqueous phase.

Published by Copernicus Publications on behalf of the European Geosciences Union. A. Baklanov et al.: Online coupled regional meteorology chemistry models in EuropeAbstract. Online coupled mesoscale meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and regional climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. Two ways of online coupling can be distinguished: online integrated and online access coupling. Online integrated models simulate meteorology and chemistry over the same grid in one model using one main time step for integration. Online access models use independent meteorology and chemistry modules that might even have different grids, but exchange meteorology and chemistry data on a regular and frequent basis. This article offers a comprehensive review of the current research status of online coupled meteorology and atmospheric chemistry modelling within Europe. Eighteen regional online coupled models developed or being used in Europe are described and compared. Topics discussed include a survey of processes relevant to the interactions between atmospheric physics, dynamics and composition; a brief overview of existing online mesoscale models and European model developments; an analysis on how feedback processes are treated in these models; numerical issues associated with coupled models; and several case studies and model performance evaluation methods. Finally, this article highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities: air quality, numerical meteorology modelling (including weather prediction) and climate modelling. This review will be of particular interest to model developers and users in all three fields as it presents a synthesis of scientific progress and provides recommendations for future research directions and priorities in the development, application and evaluation of online coupled models.

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A secondary organic aerosol (SOA) model, the Hydrophilic/Hydrophobic Organic model (H2O), is presented and evaluated over Europe. H2O uses surrogate organic molecules to represent the myriad of SOA species and distinguishes two kinds of surrogate species: hydrophilic species (which condense preferentially into an aqueous phase) and hydrophobic species (which condense only into an organic phase). These surrogate species are formed from the oxidation in the atmosphere of volatile organic compounds. H2O includes several important processes, including the effect of nitrogen oxides (NOX) on SOA formation, the dissociation of organic acids in an aqueous phase, the oligomerization of aldehydes, the non‐ideality of the particle phase and the hygroscopicity of organics. Concentrations of organic aerosols were simulated over Europe from July 2002 to July 2003 for comparison with measurements of the European Monitoring Evaluation Program (EMEP). In H2O, primary organic aerosols (POA) are considered as semi‐volatile organic compounds (SVOC) present in both the gas phase and the particle phase. Taking into account the gas‐phase fraction of SVOC increases significantly organic PM concentrations, particularly in winter, in better agreement with observations. The impacts on organic aerosol formation of ideality, of the choice of the parameterization for isoprene SOA formation, and of the OM/OC ratio of the model were also investigated. Assuming ideality in H2O was found to lead to a small decrease in OM. Compared to a two‐product parameterization, the parameterization of Couvidat and Seigneur [2011] for SOA formation from isoprene oxidation leads to a significant increase in isoprene SOA by taking into account their hydrophilic properties and suggests that most models may currently underestimate isoprene SOA.

ABSTRACT. A comparative review of algorithms currently used in air qu ality models to simulate aerosol dynamics is presented. This review addresses coagulation, condensational growth, nucleation, an d gas r r r r rparticle mass transfer. Two major approaches are used in air qu ality models to represent the particle size ( ) distribution: 1 the sectional approach in wh ich the size distribution is discretized into sections and particle properties are assumed to be constant over particle size ( ) sections and 2 the modal approach in wh ich the size distribution is approximated by several modes and particle properties are assumed to be uniform in each mode. The section al approach is accur ate for coagulation an d can reproduce the major ch aracteristics of the evolution of the particle size distribution for condensational growth with the moving-center an d hybrid algorithms. For coagulation and condensation al growth, the modal approach provides more accurate results when the standard deviations of the modes are allowed to vary than it does when they are ® xed. Predictions of H SO nucleation rates are highly sensitive to environ -2 4 mental variables and simulation of relative rates of condensation on existing particles and nucleation is a preferable approach. Explicit treatment of mass transfer is recommended for cases where volatile species undergo different equilib-( rium reactions in different particle size ranges e.g., in the presence of coarse salt ) particles . The results of this study provide useful information for use in selecting algorithms to simulate aerosol dynamics in air qu ality models and for improving the accuracy of existing algorithms.

Abstract. Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models