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ADVANCED URBANIZED METEOROLOGICAL MODELING AND AIR QUALITY SIMULATIONS WITH CMAQ AT NEIGHBORHOOD SCALES
Citation:
CHING, J. K., R. GILLIAM, S. DUPONT, AND S. BURIAN. ADVANCED URBANIZED METEOROLOGICAL MODELING AND AIR QUALITY SIMULATIONS WITH CMAQ AT NEIGHBORHOOD SCALES. Presented at NOAA/EPA Golden Jubilee, Durham, NC, September 20 - 21, 2005.
Impact/Purpose:
The objective of this task is to improve EPA's ability to accurately predict the concentrations and deposition of air pollutants in the atmosphere that are known or suspected to cause cancer or other serious health effects to humans, or adverse environmental effects. It is an essential component of EPA's National Air Toxics Assessment (NATA), which seeks to identify and quantify the concentrations and sources of those hazardous air pollutants which are of greatest potential concern, in terms of contribution to population risk. It is a major contributor to NERL's Air Toxics Research Program.
"Air toxics" or "hazardous air pollutants" (HAPs) is a category that covers a large variety of chemicals, which range from relatively non reactive to extremely reactive; can exist in the gas, aqueous, and/or particle phases; display a large range of volatilities; experience varying deposition velocities, including in some cases revolatilization; and are emitted from a wide variety of sources at a large variety of different scales. In addition, concentrations of air toxics are needed by regulators for both short (days) as well as long (up to a year) time scales. These requirements challenge our current capabilities in air quality models far beyond the needs for other pollutants, such as ozone. The specific work being done under this task involves 1.) developing and testing chemical mechanisms which are appropriate for describing the chemistry of air toxics; 2.) incorporating these chemical and physical mechanisms into EPA's CMAQ modeling system and applying the model at a variety of scales; and 3.) developing the methods for using models to predict HAPs concentrations at subgrid or neighborhood scales; and 4.) using these tools to assess the magnitude and variability of concentrations to which urban populations are exposed.
Description:
We present results from a study testing the new boundary layer parameterization method, the canopy drag approach (DA) which is designed to explicitly simulate the effects of buildings, street and tree canopies on the dynamic, thermodynamic structure and dispersion fields in urban areas. The objective is to provide realistic meteorological and air quality modeling of urban areas. This requires replacing the homogeneity in roughness and dominant land use requirements in current models with parameterizations that are based on actual surface distributions of urban morphological features. For this study, we additionally incorporate actual, within-grid land use variation with an advanced urbanized surface layer (soil atmosphere) model (SM2-U). The implementation into the NCAR-Penn State Mesoscale Meteorological Model, Version 5 (MM5) is called DA-SM-2U/MM5. Requirements for this system include gridded urban canopy parameterizations (UCP) and a canopy layer structure into the model. For this study, a set of UCPs (combination of vertical profiles and surface values), gridded at 1 km was derived from a set of 3-D high resolution (order 1m) buildings and vegetation data. For our study, the data came from airborne lidar measurements, ancillary data from satellites, high altitude photography, as well as detailed residential, commercial and industrial maps.
Standard, coarse scale MM5 runs were performed at 36, 12, and 4 km grid sizes, the latter used to perform the simulations at 1 km grid size using both the drag approach (DA-SM2U) and for comparative purposes, the standard, roughness based approach (RA). These multi-scale meteorology fields were then used to simulate air quality using the USEPA's Community Multiscale Air Quality (CMAQ) Model. Considerable differences in the transport, in the characterization of the urban heat island and ultimately in the air quality simulations are apparent. The observations support the use of the advanced approach.