Keywords
atmospheric modeling, air quality
Start Date
1-7-2006 12:00 AM
Abstract
Air quality modeling is an area with a significant progress and interest during the last two decades. It covers all aspects related to pollution dispersion and impact on different ecosystems. It is very much related to the meteorological field since the atmosphere is governed by the general laws derived by the Navier-Stokes equation system. Progress in computer capabilities during the last decades has impulse substantially the research on air quality modeling in a parallel way. Air pollution modeling covers a very complex and interdisciplinary area where we include remote sensing – land use impact -, initial and boundary conditions, data assimilation techniques, chemical schemes, comparison between measured and modeled data, computer efficiency, parallel computing in air quality modeling, long-range transport impact on local air pollution, new satellite data assimilation techniques, real-time and forecasting air quality modeling and sensitivity analysis. This contribution focuses on providing a general overview of the state-of-the-art on air quality modeling, from the point of view of the “user community”, i.e. policy makers, urban planners, environmental managers, etc.. It also tries to bring to the discussion key questions concerning the air quality modeling success in usage, such as, where are greatest uncertainties in emission inventories, how well do air quality models simulate urban aerosols, what are the next generation developments in models to answer new scientific questions, etc.
AIR QUALITY MODELLING: STATE-OF-THE-ART
Air quality modeling is an area with a significant progress and interest during the last two decades. It covers all aspects related to pollution dispersion and impact on different ecosystems. It is very much related to the meteorological field since the atmosphere is governed by the general laws derived by the Navier-Stokes equation system. Progress in computer capabilities during the last decades has impulse substantially the research on air quality modeling in a parallel way. Air pollution modeling covers a very complex and interdisciplinary area where we include remote sensing – land use impact -, initial and boundary conditions, data assimilation techniques, chemical schemes, comparison between measured and modeled data, computer efficiency, parallel computing in air quality modeling, long-range transport impact on local air pollution, new satellite data assimilation techniques, real-time and forecasting air quality modeling and sensitivity analysis. This contribution focuses on providing a general overview of the state-of-the-art on air quality modeling, from the point of view of the “user community”, i.e. policy makers, urban planners, environmental managers, etc.. It also tries to bring to the discussion key questions concerning the air quality modeling success in usage, such as, where are greatest uncertainties in emission inventories, how well do air quality models simulate urban aerosols, what are the next generation developments in models to answer new scientific questions, etc.
