Particulate Matter Modeling in the Los Angeles Basin Using SAQM-AERO

Abstract

The SARMAP air quality model, enhanced with aerosol modeling capability, and its associated components were developed to understand causes of ozone (O3) and particulate matter exceedances in the San Joaquin Valley of California. In order for this modeling system to gain increasing acceptance and use in guiding air quality management, it is important to assess how transportable this modeling system is across geographic domains. We describe the first application of the modeling system outside the "home" domain for which it was developed and evaluated. We have chosen the August 27-28, 1987, intensive monitoring period of the Southern California Air Quality Study to evaluate the performance of the modeling system and to assess its sensitivity to emission control options. The predicted surface concentrations of O3 and other gas-phase species were spatially and temporally correlated with measured data. The fractional normalized absolute error was 0.32 to 0.36 for O3, and somewhat larger for other species. The fractional normalized bias for O3 on August 27 and 28, 1987, was 0.02 to 0.04. The simulated PM2.5 mass and constituent species concentrations reproduced the magnitude and variability of the observed daytime concentrations at most locations; however, nighttime PM2.5 concentrations were overpredicted by the model. The model's response to emission control options was consistent with other models of the same genre.

Current Status of Air Quality Models for Particulate Matter

“…Figure 1 depicts the various components of the PM module of a 3-D Eulerian air quality model. Gas-phase chemistry is a key component because it governs the amount of condensable species [e.g., H 2 SO 4 , HNO 3 , and secondary organic aerosol (SOA)] being formed. Similarly, aqueousphase chemistry governs the amount of chemical species formed in cloud and fog droplets; some of those species will remain in the particulate phase as the droplets evaporate.…”

“…However, many condensable species (e.g., HNO 3 , SOA) will partition between the gas phase and the particulate phase according to their gas-phase concentration, the concentration of other species (e.g., NH 3 in the case of NO 3 -), the chemical composition of the particles, temperature, pressure, and relative humidity. It is essential to simulate this partitioning correctly because it determines the PM 2.5 concentration and chemical composition.…”

“…Although box models and Lagrangian models can serve a useful purpose for a specific application, the need to cover large domains makes 3-D Eulerian grid-based models the most suited to simulate chemical transformations and transport processes over such domains. Many 3-D Eulerian models have been developed for O 3 formation and acid deposition, and some of those models have been extended to simulate PM formation.…”

“…Comprehensive reviews of 3-D Eulerian models for O 3 8 and acid deposition 9 have been conducted recently. We focus here on 3-D Eulerian models for PM 2.5 .…”

“…Such relationships can be quite complex because of the nonlinear nature of the atmospheric chemistry of oxidant and acid formation. [1][2][3] Therefore, the development of effective emission control strategies will require mathematical models that can adequately describe these relationships between emissions and PM 2.5 concentrations.…”