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%.

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[1] A unified model framework with online-coupled meteorology and chemistry and consistent model treatments across spatial scales is required to realistically simulate chemistry-aerosol-cloud-radiation-precipitation-climate interactions. In this work, a global-through-urban WRF/Chem model (i.e., GU-WRF/Chem) has been developed to provide such a unified model framework to simulate these important interactions across a wide range of spatial scales while reducing uncertainties from the use of offline-coupled model systems with inconsistent model treatments. Evaluation against available observations shows that GU-WRF/Chem is capable of reproducing observations with comparable or superior fidelity than existing mesoscale models. The net effect of atmospheric aerosols is to decrease shortwave and longwave radiation, NO 2 photolysis rate, near-surface temperature, wind speed at 10-m, planetary boundary layer height, and precipitation as well as to increase relative humidity at 2-m, aerosol optical depths, column cloud condensation nuclei, cloud optical thickness, and cloud droplet number concentrations at all scales. As expected, such feedbacks also change the abundance and lifetimes of chemical species through changing radiation, atmospheric stability, and the rates of many meteorologically-dependent chemical and microphysical processes. The use of higher resolutions in progressively nested domains from the global to local scale notably improves the model performance of some model predictions (especially for chemical predictions) and also captures spatial variability of aerosol feedbacks that cannot be simulated at a coarser grid resolution. Simulated aerosol, radiation, and cloud properties exhibit small-to-high sensitivity to various nucleation and aerosol activation parameterizations. Representing one of the few unified global-through-urban models, GU-WRF/Chem can be applied to simulate air quality and its interactions with meteorology and climate and to quantify the impact of global change on urban/regional air quality across various spatial scales.Citation: Zhang, Y., P. Karamchandani, T. Glotfelty, D. G. Streets, G. Grell, A. Nenes, F. Yu, and R. Bennartz (2012), Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem),

[1] We describe the development, evaluation, and application of a new plume-in-grid model for investigating the subgrid-scale effects, associated with NO x emissions from large elevated point sources, on O 3 formation. Traditional Eulerian air quality models cannot resolve the strong concentration gradients created by plumes emitted from large point sources. Although several plume-in-grid approaches have been used in the past to address this issue, they have been limited by their simplistic simulation of plume dispersion and/or chemistry and their lack of treatment of the effect of turbulence on plume chemistry. In the plume-in-grid model presented here, the embedded reactive plume model combines a state-of-the-science puff model with a gas-phase chemistry mechanism that is consistent with that used in the host grid model. The puff model uses a second-order closure scheme, allowing for a more accurate treatment of dispersion and the influence of turbulent concentration fluctuations on chemical rates. It also allows the splitting and merging of puffs to account for wind shear effects, varying chemistry across the plume, and interplume and intraplume interactions. The combined puff/chemistry model is embedded into an Eulerian grid model. Results from the application of this model to the northeastern United States, a domain containing some of the largest NO x -emitting power plants in the United States, show that the plume-in-grid treatment leads to significant differences in surface O 3 and HNO 3 concentrations.

[1] An existing plume-in-grid model for ozone and particulate matter, which provides an explicit treatment of stack plumes embedded within a three-dimensional grid-based Eulerian air quality model, is extended to include a comprehensive treatment of mercury (Hg) processes. The model is applied to the continental United States to investigate the subgrid-scale effects associated with Hg emissions from large elevated point sources on atmospheric Hg concentrations and deposition. The top thirty Hg-emitting power plants in the U.S. were selected for explicit plume-in-grid treatment. Two new processes are included in the Hg chemical mechanism: the gas-phase adsorption of reactive gaseous mercury (RGM) on atmospheric particulate matter and the reduction of RGM to elemental Hg by sulfur dioxide. The plume-in-grid treatment results in improved performance for Hg wet deposition over a purely Eulerian grid-based model, partial correction of overpredictions of wet deposition downwind of coal-fired power plants in the northeastern U.S., and decreases of approximately 10% in simulated dry and wet deposition over large parts of the eastern U.S., with larger decreases near the plants selected for plume-in-grid treatment. On average, 23% of ambient RGM is modeled to adsorb on atmospheric particulate matter.