Classification of weather patterns and improvement of meteorological inputs for TexAQS-II air quality simulations.

摘要

The Houston/Galveston area has been designated ozone non-attainment by the U.S. EPA according to the 8-hour ozone standard. The complicated meteorological phenomenon of the coastal urban area is one of the big challenges for simulating regional air quality. An accurate input of weather conditions is required to describe transport of air pollutants and development of ozone. The goal of this dissertation is to improve meteorological inputs for air quality modeling. We focus on three distinctive research areas (1) classification of weather patterns affecting air quality, (2) improvement of meteorological inputs through data assimilation, and (3) linkage of meteorological and chemical models.Through the cluster analysis, we intended to understand how synoptic weather pattern influences the nature and characteristics of sea-breeze circulation that affect air quality in the HGA and to improve air quality forecasting capability. Through trajectory analyses, we have identified how different weather patterns affect pollutant source-receptor relationships. We improved the data assimilation system by applying a multi-stage objective analysis of extensive meteorological observations. We demonstrated that the re-assimilated meteorological inputs from the MUltiscale Nest-down Data Assimilation System (MUNDAS) improved the CMAQ air quality simulation results for the 2006 Second Texas Air Quality Study (TexAQS-II). Utilizing the Weather Research and Forecasting modeling system (WRF) and the Community Multiscale Air Quality model (CMAQ), we evaluated the impact of meteorological input intervals on air quality modeling. We also examined the weaknesses and limitations of the off-line coupling mode between the two systems. Results showed that the mass conservation properties in CMAQ between the 15-minute and 1-hour interval meteorological inputs are similar demonstrating that the off-line coupling paradigm can characterize pollutant transport in air quality modeling as long as the variability of the meteorological event is properly represented by the input frequency.