Modeling Air Quality During The California Regional Pm_(10)/pm_(2.5) Air Quality Study (crpaqs) Using The Ucd/cit Source-oriented Air Quality Model - Part I. Base Case Model Results

摘要

A comprehensive air quality modeling project was carried out to simulate size and composition resolved airborne particulate matter concentrations in northern and central California using the pollutant concentration and meteorological data collected during the California Regional PM_(10)/PM_(2.5) Air Quality Study (CRPAQS) from December 15, 2000 to January 7, 2001. Measured 24-h average PM_(2.5) concentrations during this time period exceeded 180 μm~(-3) at Bakersfield, making it the most severe PM_(2.5) air quality episode ever recorded in the United States with a rigorous measurement database to support modeling. In this paper, the UCD/CIT source-oriented air quality model is used to predict the concentrations of O_3, NO, NO_2, CO, elemental carbon (EC), organic compounds (OC), nitrate and PM_(2.5) mass concentration over a 24-day period using a horizontal resolution of 4 km × 4 km to cover all of central California. This is the first extensive evaluation of an air quality model in central California using the fine spatial resolution appropriate for the mountain-valley topography of the region combined with the relatively long multi-week time scales associated with winter stagnation events. Fractional bias (FB) values were calculated at all sites on each day of the study to quantify model performance. The CO (FB = -0.5 to +0.3), O_3 (FB = -0.5 to +0.25), NO (FB = -0.9 to -0.1) and NO_2 (FB = 0 to +0.4) concentrations predicted by the UCD/CIT model are in general agreement with observations at most monitoring stations throughout the Valley. The predicted PM_(2.5) concentrations (FB = -0.5 to +0.75) generally agree with observations at Bethel Island, Sacramento, Fresno and Bakersfield spanning the entire length of the model domain. PM_(2.5) concentrations are over-predicted at the remote monitoring site Angiola in the central portion of the domain. Part of the over-prediction is due to excess fugitive dust emissions. CO, NO, EC and OC were all under-predicted at Angiola, indicating possible missing combustion sources in the emission inventory. The regional nitrate (FB = -1.5 to +1.25) formation dynamics were correctly reproduced by the model simulation but imperfect wind fields cause differences between the predicted vs. measured spatial distribution of nitrate during the last several days of simulation leading to the broader range of fraction bias. Overall, the results of the current study confirm the ability of the air quality model to capture the major features of a severe particulate air pollution event in northern and central California providing a foundation for future studies on source apportionment and emissions control.