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Experiments were performed during the period May–July of 1993 at Summit, Greenland. Aerosol mass size distributions as well as daily average concentrations of several anionic and cationic species were measured. Dry deposition velocities for SO42− were estimated using surrogate surfaces (symmetric airfoils) as well as impactor data. Real‐time concentrations of particles greater than 0.5 μm and greater than 0.01 μm were measured. Snow and fog samples from nearly all of the events occurring during the field season were collected. Filter sampler results indicate that SO42− is the dominant aerosol anion species, with Na+, NH4+, and Ca2+ being the dominant cations. Impactor results indicate that MSA and SO42− have similar mass size distributions. Furthermore, MSA and SO42− have mass in both the accumulation and coarse modes. A limited number of samples for NH4+ indicate that it exists in the accumulation mode. Na, K, Mg, and Ca exist primarily in the coarse mode. Dry deposition velocities estimated from impactor samples and a theory for dry deposition to snow range from 0.017 cm/s +/− 0.011 cm/s for NH4+ to 0.110 cm/s +/− 0.021 cm/s for Ca. SO42− dry deposition velocity estimates using airfoils are in the range 0.023 cm/s to 0.062 cm/s, as much as 60% greater than values calculated using the airborne size distribution data. The rough agreement between the airfoil and impactor‐estimated dry deposition velocities suggests that the airfoils may be used to approximate the dry deposition to the snow surface. Laser particle counter (LPC) results show that particles > 0.5 μm in diameter efficiently serve as nuclei to form fog droplets. Condensation nuclei (CN) measurements indicate that particles < 0.5 μm are not as greatly affected by fog. Furthermore, impactor measurements suggest that from 50% to 80% of the aerosol SO42− serves as nuclei for fog droplets. Snow deposition is the dominant mechanism transporting chemicals to the ice sheet. For NO3−, a species that apparently exists primarily in the gas phase as HNO3(g), 93% of the seasonal inventory (mass of a deposited chemical species per unit area during the season) is due to snow deposition, which suggests efficient scavenging of HNO3(g) by snowflakes. The contribution of snow deposition to the seasonal inventories of aerosols ranges from 45% for MSA to 76% for NH4+. The contribution of fog to the seasonal inventories ranges from 13% for Na+ and Ca2+ to 26% and 32% for SO42− and MSA. The dry deposition contribution to the seasonal inventories of the aerosol species is as low as 5% for NH4+ and as high as 23% for MSA. The seasonal inventory estimations do not take into consideration the spatial variability caused by blowing and drifting snow. Overall, results indicate that snow deposition of chemical species is the dominant flux mechanism during the summer at Summit and that all three deposition processes should be considered when estimating atmospheric concentrations based on ice core chemical signals.

Abstract. The seasonal variation in atmospheric transport patterns to Summit, Greenland, is examined using a 44-year record of daily, 10-day, isobaric back trajectories at the 500-hPa level. Over 24,000 modeled trajectories are aggregated into distinct patterns using cluster analysis. Ten-day trajectories reaching Summit are longest during winter, with 67% extending upwind (westward) as far back as Asia or Europe. Trajectories are shortest during summer, with 46% having 10-day origins over North America. During all seasons a small percentage (3-7%) of trajectories originate in west Asia/Europe and follow a meridional path over the Arctic Ocean before approaching Summit from the northwest. Trajectories at the 700-hPa level tend to be shorter than at 500 hPa, with many of the 700-hPa trajectories from North America tracking over the North Atlantic and approaching Summit from the south. The long-range transport climatology for Summit is similar to a year-round climatology prepared for Dye 3, located 900 km to the south [Davidson et al., 1993b]. An analysis of several aerosol species measured at Summit during summer 1994 reveals examples of the usefulness and also the limitations of using long-range air trajectories to interpret chemical data.

The Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study was commissioned to investigate the sources of haze at Big Bend National Park in southwest Texas. The modeling domain of the BRAVO Study includes most of the continental United States and Mexico. The BRAVO emissions inventory was constructed from the 1999 National Emission Inventory for the United States, modified to include finer-resolution data for Texas and 13 U.S. states in close proximity. The first regional-scale Mexican emissions inventory designed for air-quality modeling applications was developed for 10 northern Mexican states, the Tula Industrial Park in the state of Hidalgo, and the Popocatépetl volcano in the state of Puebla. Emissions data were compiled from numerous sources, including the U.S. Environmental Protection Agency (EPA), the Texas Natural Resources Conservation Commission (now Texas Commission on Environmental Quality), the Eastern Research Group, the Minerals Management Service, the Instituto Nacional de Ecología, and the Instituto Nacional de Estadistica Geografía y Informática. The inventory includes emissions for CO, nitrogen oxides, sulfur dioxide, volatile organic compounds (VOCs), ammonia, particulate matter (PM) < 10 microm in aerodynamic diameter, and PM < 2.5 microm in aerodynamic diameter. Wind-blown dust and biomass burning were not included in the inventory, although high concentrations of dust and organic PM attributed to biomass burning have been observed at Big Bend National Park. The SMOKE modeling system was used to generate gridded emissions fields for use with the Regional Modeling System for Aerosols and Deposition (REMSAD) and the Community Multiscale Air Quality model modified with the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (CMAQ-MADRID). The compilation of the inventory, supporting model input data, and issues encountered during the development of the inventory are documented. A comparison of the BRAVO emissions inventory for Mexico with other emerging Mexican emission inventories illustrates their uncertainty.