An integrated air pollution modeling system for urban and regional scales: 2. Simulations for SCAQS 1987

Abstract

A new air quality modeling system, the surface meteorology and ozone generation (SMOG) model, is used to investigate the evolution and properties of air pollution in the Los Angeles basin during the southern California air quality study (SCAQS) intensive field program. The SMOG model includes four major components: a meteorological model, a tracer transport code, a chemistry and aerosol microphysics model, and a radiative transfer code. The fidelity of the coupled modeling system is evaluated by comparing model predictions against SCAQS data. Predictions of surface winds and temperatures are found to be in excellent agreement with measurements during daylight hours, when a strong sea breeze and mountain‐upslope flows are predominant but are less reliable at night when winds are typically lighter and more variable. Winds aloft, including shear and temporal variations, are also simulated quite well, although the forecasts (which are not constrained through continuous data assimilation) tend to drift from actual conditions as time progresses. Accordingly, the large‐scale flow is reinitialized each morning in the simulations. The dispersion patterns of two inert tracers released during the SCAQS period are accurately reproduced by the model. The two releases, one in the early morning hours and one around noon, led to quite different transport rates and distributions owing to the evolution of the sea breeze over die course of the day. Overall, the three‐dimensional development of thermally induced winds and their influences on tracer transport in the Los Angeles basin are accurately captured by the model. The predicted surface concentrations of ozone and other key pollutants have been spatially and temporally correlated with measured abundance, and the values agree to within 25–30% for ozone, with somewhat larger mean differences for several other species. In the case of the vertical distribution of ozone, the SMOG simulations generate dense oxidant (ozone) layers embedded in the temperature inversion, explaining for the first time similar features seen during SCAQS. Sources of error and uncertainty in the simulations are identified and discussed. The broad agreement between SMOG model predictions and SCAQS observations suggests that an integrated modeling approach is well suited for representing the coupled effects of mesoscale meteorology, tracer dispersion, and chemical transformations on urban and regional air quality.