tions observed within the urban area are the best measures of air quality for use in designing control strategies.
A New Modeling Approach. The use of new Cray Research supercomputers permits simulations predicated on a different approach to modeling that were formerly computationally infeasible. Current photochemical airshed models accurately describe the physical and chemical processes responsible for chemical transformation, transport, and fate. Advances in computational technology now permit the exploration of more control scenarios at a greater number of sites at smaller time intervals. Considering the entire Los Angeles basin as a rectangular grid 200 by 100 kilometers, 45 different combinations of control levels (most of them limited to 80 percent or less of an improvement over current standards, those more likely to be implemented over the next decade) were simulated under expected atmospheric conditions for thousands of adjacent but discrete locations within the shed over a 2-day period, each simulation requiring 40 minutes of computer time. The choice of issues and methods was designed to widen the applicability of the model to other urban locations.
The model must first demonstrate its reliability by reproducing air quality outcomes and readings for O3, NO2, HNO3, NH4NO3, and PAN that were historically experienced. August 30 and 31, 1982, were chosen for this purpose for a number of meteorological reasons. When compared to the data collected for those days, the model's performance was in excellent agreement for ozone and PAN, and for nitrogen dioxide was better than with previous models. Also, the gas-phase and particulate predictions were in excellent agreement with observations. This base-case performance established the model's reliability, and simulations of differing control strategies were run.
The Results and Implications for Control Strategies. A number of surprising spatial patterns were observed for the first time, as this modeling technique revealed interactions and time-sensitive patterns for the targeted substances that had not been captured by previous models. In particular, the model demonstrated that changing relative emissions standards very often had the impact not of reducing peak ozone concentrations, but of merely moving them to a different region within the airshed. Another strongly supported observation involves the effect of reductions of emissions on concentrations of other pollutants, such as PAN and inorganic nitrate. The modeling seems to suggest several important premises for regulators trying to balance the cost and effectiveness of control strategies: