Regional variations in sulfate and nitrate on annual, seasonal, and synoptic time scales.

Ambient data from Interagency Monitoring of Protected Visual Environments (IMPROVE) monitors are analyzed to evaluate the spatial structure of SO4 and NO3 aerosols in the mid-Atlantic region. Sub-weekly, seasonal, and annual data values are compared between the IMPROVE Washington, DC, site and three rural sites. Synoptic perturbations are compared between sites to quantify similarities in short-term temporal perturbations of SO4 and NO3. Based on these comparisons between the rural and urban IMPROVE monitors, the spatial structure of SO4 shows broad regional homogeneity that is recognizable from both the long-term average values and the short-term variations. NO3 data on a seasonal and annual basis show much larger spatial gradients between the urban Washington monitor and the three rural monitors than do SO4 data. Short-term NO3 perturbations at the three rural monitors also differ significantly from those at the Washington site. These dissimilarities in NO3 levels between the rural and urban IMPROVE monitors on both short-term and longer-term time scales indicate little homogeneity of NO3 aerosols in the mid-Atlantic region considered here. The volatility of NO3 aerosols and the removal rate of HNO3 via dry deposition could contribute to the spatial variability differences shown here between SO4 and NO3.

Developing seasonal ammonia emission estimates with an inverse modeling technique.

Significant uncertainty exists in magnitude and variability of ammonia (NH3) emissions, which are needed for air quality modeling of aerosols and deposition of nitrogen compounds. Approximately 85% of NH3 emissions are estimated to come from agricultural nonpoint sources. We suspect a strong seasonal pattern in NH 3 emissions; however, current NH3 emission inventories lack intra-annual variability. Annually averaged NH 3 emissions could significantly affect model-predicted concentrations and wet and dry deposition of nitrogen-containing compounds. We apply a Kalman filter inverse modeling technique to deduce monthly NH3 emissions for the eastern U.S. Final products of this research will include monthly emissions estimates from each season. Results for January and June 1990 are currently available and are presented here. The U.S. Environmental Protection Agency (USEPA) Community Multiscale Air Quality (CMAQ) model and ammonium (NH4+) wet concentration data from the National Atmospheric Deposition Program (NADP) network are used. The inverse modeling technique estimates the emission adjustments that provide optimal modeled results with respect to wet NH4+ concentrations, observational data error, and emission uncertainty. Our results suggest that annual average NH 3 emissions estimates should be decreased by 64% for January 1990 and increased by 25% for June 1990. These results illustrate the strong differences that are anticipated for NH3 emissions.