The Australian Air Quality Forecasting System. Part I: Project Description and Early Outcomes (original) (raw)
Related papers
2005
The Australian Air Quality Forecasting System (AAQFS) is currently under development. The numerical system will produce high-resolution, meteorological and air quality forecasts for the major urban areas of Australia, and will initially be tested in Melbourne and then demonstrated in Sydney during the 2000 Olympics. The AAQFS will be used to generate twice daily, 24-36 hour air quality forecasts at an effective resolution of a few kilometres. A range of air pollutants will be forecast, including photochemical smog, fine particulate matter and air toxics. The air quality forecasts will be provided to the EPAs, greatly enhancing their ability to provide relevant air quality information to the public. Here, we provide a brief description of the design and current status of AAQFS development, and present examples of system operation for the Sydney region.
An integrated air quality forecast system for a metropolitan area
2011
Air quality forecasting is an important issue in environmental research, due to the effects that air pollutants have on population health. To deal with this topic, in this work an integrated modelling system has been developed to forecast daily maximum eight hours ozone concentrations and daily mean PM10 concentrations, up to two days in advance, over an urban area. The presented approach involves two steps. In the first step, artificial neural networks are identified and applied to get point-wise forecasting.
Atmosphere
The ability of meteorological models to accurately characterise regional meteorology plays a crucial role in the performance of photochemical simulations of air pollution. As part of the research funded by the Australian government’s Department of the Environment Clean Air and Urban Landscape hub, this study set out to complete an intercomparison of air quality models over the Sydney region. This intercomparison would test existing modelling capabilities, identify any problems and provide the necessary validation of models in the region. The first component of the intercomparison study was to assess the ability of the models to reproduce meteorological observations, since it is a significant driver of air quality. To evaluate the meteorological component of these air quality modelling systems, seven different simulations based on varying configurations of inputs, integrations and physical parameterizations of two meteorological models (the Weather Research and Forecasting (WRF) and ...