An updated modeling framework to simulate Los Angeles air quality – Part 1: Model development, evaluation, and source apportionment

Abstract

Abstract. This study describes a modeling framework, model evaluation, and source apportionment to understand the causes of Los Angeles (LA) air pollution. A few major updates are applied to the Community Multiscale Air Quality (CMAQ) model with a high spatial resolution (1 km × 1 km). The updates include dynamic traffic emissions based on real-time, on-road information and recent emission factors and secondary organic aerosol (SOA) schemes to represent volatile chemical products (VCPs). Meteorology is well predicted compared to ground-based observations, and the emission rates from multiple sources (i.e., on-road, volatile chemical products, area, point, biogenic, and sea spray) are quantified. Evaluation of the CMAQ model shows that ozone is well predicted despite inaccuracies in nitrogen oxide (NOx) predictions. Particle matter (PM) is underpredicted compared to concurrent measurements made with an aerosol mass spectrometer (AMS) in Pasadena. Inorganic aerosol is well predicted, while SOA is underpredicted. Modeled SOA consists of mostly organic nitrates and products from oxidation of alkane-like intermediate volatility organic compounds (IVOCs) and has missing components that behave like less-oxidized oxygenated organic aerosol (LO-OOA). Source apportionment demonstrates that the urban areas of the LA Basin and vicinity are NOx-saturated (VOC-sensitive), with the largest sensitivity of O3 to changes in VOCs in the urban core. Differing oxidative capacities in different regions impact the nonlinear chemistry leading to PM and SOA formation, which is quantified in this study.