Advanced air quality modeling system for the simulation of photochemical ozone formation over North Carolina
- MCNC-North Carolina Supercomputing Center, Research Triangle Park, NC (United States)
- North Carolina Dept. of Environment and Natural Resources, Raleigh, NC (United States). Div. of Air Quality
- Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Environmental Sciences and Engineering
An advanced air quality modeling system is used to simulate the formation of photochemical oxidants, mainly ozone, over North Carolina. The objective of this modeling study is to successfully model the formation processes of ozone in North Carolina to lead to effective ozone control strategy developments for both 1-hour and 8-hour standards and eventually to address the particulate matter issue. The modeling system selected for this ongoing project is the North Carolina Supercomputing Center`s Environmental Decision Support System (EDSS), which evolved from a working prototype of EPA`s Third Generation Modeling System, or Models-3. The EDSS consists of three major modeling components : the Multiscale Air Quality SImulation Platform (MAQSIP) for chemistry/transport modeling, Mesoscale Model Version 5 (MM5) for meteorological modeling, and Sparse Matrix Operator Kernel Emissions (SMOKE) system for emission modeling. Two inner subdomains at 12-km and 4-km grid resolutions centered over Charlotte are nested inside a coarse domain at a 36-km resolution. Sixteen vertical layers with a denser grid at lower altitude are used to better resolve the mixing layer. The CB-IV chemistry mechanism with updated isoprene chemistry and radical-radical reactions is used to simulate the chemical transformations of reacting species. Preliminary results show that the MAQSIP has reasonably simulated the temporal and spatial distribution of ozone as compared to observations in the first 6-day episode during July 10--15, 1995. Improved ozone predictions are shown in the model using finer grid resolution. Various ozone sensitivity studies on the model inputs such as initial and boundary conditions and the existence of clouds are under testing. An innovative analysis tool for model evaluation and error detection, the Process Analysis method, is also applied to help understand the regulating processes that lead to formation of ozone.
- OSTI ID:
- 362021
- Report Number(s):
- CONF-980632--
- Country of Publication:
- United States
- Language:
- English
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