Air Quality Modeling and Forecasting

Air quality models help explain how pollutants are transported, transformed, and dispersed in the atmosphere. They are useful for analyzing past air pollution episodes and future scenarios that account for changes in emissions and climate, as well as assessing the effectiveness of emission mitigation strategies. A well-tuned air quality model can be run on a daily basis to forecast air quality conditions in the following days, informing the public of potentially harmful levels of atmospheric pollution. However, despite the valuable information that air quality models can provide, no Southeast Asian country has implemented a modeling system as part of its air quality management. Air quality models for Southeast Asia have been run by local and international researchers. This chapter describes the Eulerian, Lagrangian, and hybrid models, as well as machine-learning algorithmsAir quality modelingmachine learning algorithms, that they have used to answer specific questions about the impact of specific emission sources, such as biomass burning, on individual subregions or the entire region, or to investigate the atmospheric processes that drive air pollution at the province or city scale. It also reviews global and regional air quality forecast modelsAir quality modelingforecast models developed and operated by international consortia as alternatives to air quality forecasting in Southeast Asia.