ABSTRACT
Air pollution is a serious environmental issue in Southeast Asian (SEA) countries because of its effects on human health and climate. Nevertheless, air pollution data, i.e., particulate matter (PM) that can describe the spatiotemporal dynamics of pollution, are not readily available in this region due to fewer monitoring stations. Alternatively, aerosol optical depth (AOD) data from the ground measurements and satellite data are widely used by the scientific community. To date, numerous satellite data and methods are available for obtaining spatially and temporarily continuous PM data. In this chapter, we provide a detailed review of both the AOD data sources that can be used to retrieve PM and the methods. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership and Advanced Himawari Imager (AHI) aboard Himawari-8 are among the latest data that provide AOD data with acceptable accuracy when compared with the ground-based AOD measurements. These satellites offer AOD products with better spatial (5–7 km) and temporal (hourly) resolutions that characterize PM variations in the Southeast Asian region. AOD data from the satellites coupled with meteorology, land use, and anthropogenic emissions can be effectively used to estimate PM levels in the atmosphere. There are numerous techniques available to assess PM, and they can generally be grouped into scaling factor models, physical analysis models, geostatistical interpolation techniques, and empirical statistical models. Among these models, statistical models are flexible since various datasets can be integrated to provide better estimates of PM over SEA. Advanced statistical models such as support vector regression, generalized additive model, and hierarchal models are not tested robustly in this region; thus, we infer the need to explore these models to provide better PM estimates in SEA.
