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[ 1 ] An atmospheric mercury model intercomparison study has been conducted to compare three regional-scale atmospheric mercury models, CMAQ, REMSAD, and TEAM, in atightly constrained testing environment with afocus on North America. Each of these models used the same horizontal modeling grid, pollutant emission information, modeled meteorology,a nd boundary conditions to the greatest extent practical. Three global-scale atmospheric mercury models were applied to define three separate initial condition and boundary condition (IC/BC) data sets for elemental mercury,r eactive gaseous mercury,a nd particulate mercury air concentrations for use by the regional-scale models. The monthly average boundary concentrations of some mercury species simulated by the global models were found to vary by more than afactor of 10, especially at high altitudes. CMAQ, REMSAD, and TEAM were each applied three times, once for each IC/BC data set, to simulate atmospheric mercury transport and deposition during 2001. This paper describes the study design and shows qualitative model-to-model comparisons of simulation results on an annual basis. The air concentration patterns for mercury simulated by the regional-scale models showed significant differences even when the same IC/BC data set was used. Simulated wet deposition of mercury was strongly influenced by the shared precipitation data, but differences of over 50% were still apparent. Simulated dry deposition of mercury was found to vary between the regional-scale models by nearly af actor of 10 in some locations. Further analysis is underway to perform statistical comparisons of simulated and observed mercury wet deposition using weekly and annual sample integration periods.

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Abstract. This study presents the results from two sets of 18-year air quality simulations over the Northeastern US performed with a regional photochemical modeling system. These two simulations utilize different sets of lateral boundary conditions, one corresponding to a time-invariant climatological vertical profile and the other derived from monthly mean concentrations extracted from archived ECHAM5-MOZART global simulations. The objective is to provide illustrative examples of how model performance in several key aspects -trends, intra-and interannual variability of groundlevel ozone, and ozone/precursor relationships -can be evaluated against available observations, and to identify key inputs and processes that need to be considered when performing and improving such long-term simulations. To this end, several methods for comparing observed and simulated trends and variability of ground level ozone concentrations, ozone precursors and ozone/precursor relationships are introduced. The application of these methods to the simulation using time-invariant boundary conditions reveals that the observed downward trend in the upper percentiles of summertime ozone concentrations is captured by the model in both directionality and magnitude. However, for lower percentiles there is a marked disagreement between observed and simulated trends. In terms of variability, the simulations using the time-invariant boundary conditions underestimate observedCorrespondence to: C. Hogrefe (chogrefe@dec.state.ny.us) inter-annual variability by 30%-50% depending on the percentiles of the distribution. The use of boundary conditions from the ECHAM5-MOZART simulations improves the representation of interannual variability but has an adverse impact on the simulated ozone trends. Moreover, biases in the global simulations have the potential to significantly affect ozone simulations throughout the modeling domain, both at the surface and aloft. The comparison of both simulations highlights the significant impact lateral boundary conditions can have on a regional air quality model's ability to simulate long-term ozone variability and trends, especially for the lower percentiles of the ozone distribution.

[1] A previous intercomparison of atmospheric mercury models in North America has been extended to compare simulated and observed wet deposition of mercury. Three regional-scale atmospheric mercury models were tested: the Community Multiscale Air Quality (CMAQ) model, the Regional Modeling System for Aerosols and Deposition (REMSAD), and the Trace Element Analysis Model (TEAM). These models were each employed using three sets of lateral boundary conditions to test their sensitivity to intercontinental transport of mercury. The same meteorological and pollutant emission data were used in each simulation. Observations of wet deposition were obtained from the National Atmospheric Deposition Program's Mercury Deposition Network. The regional models can explain 50-70% of the site-to-site variance in annual mercury wet deposition. CMAQ was found to have slightly superior agreement with observations of annual mercury deposition flux in terms of the mean value for all monitoring sites, but REMSAD showed the best correlation when measured by the coefficient of determination (r 2 ). With the exception of one CMAQ simulation, all of the models tended to simulate more wet deposition of mercury than was observed. TEAM exceeded the observed average annual wet deposition by 50% or more in all three of its simulations. CMAQ and REMSAD were better able to reproduce the observed seasonal distribution of mercury wet deposition than was TEAM, but TEAM showed the highest correlation for weekly wet deposition samples. An analysis of model accuracy at each observation site showed no obvious geographic patterns for correlation, bias, or error. Adjusting simulated mercury deposition on the basis of the difference between observed and simulated precipitation data improved the correlation and error scores for all of the models.

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The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM 2.5 ) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NO x ). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NO x emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM 2.5 , the differences were 0.1-0.25 g/m 3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM 2.5 NAAQS of 15 g/m 3 . Spatial variations in the ozone and PM 2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM 2.5 levels are dependent on ambient levels of anthropogenic emissions.