Abstract. The role of biogenic hydrocarbons on ozone modeling has been a controversial issue since the 1970s. In recent years, changes in biogenic emission algorithms have resulted in large increases in estimated isoprene emissions. This paper describes a recent algorithm, the second generation of the Biogenic Emissions Inventory System (BEIS2). A sensitivity analysis is performed with the Regional Acid Deposition Model (RADM) to examine how increased isoprene emissions generated with BEIS2 can influence the modeling of elevated ozone concentrations and the response of ozone to changes to volatile organic compound (VOC) and nitrogen oxide (NOx) emissions across much of eastern North America. Increased isoprene emissions are found to produce a predicted shift in elevated ozone concentrations from VOC sensitivity to NOx sensitivity over many areas of eastern North America. Isoprene concentrations measured near Scotia, Pennsylvania, during the summer of 1988 are compared with RADM estimates of isoprene and provide support for the veracity of the higher isoprene emissions in BEIS2, which are about a factor of 5 higher than BEIS 1 during warm, sunny conditions.

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 NH3 emissions; however, current NH3 emission inventories lack intra-annual variability. Annually averaged NH3 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 NH3 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.