Research Institute of Climate, Energy and Environment Convergence and Graduate School of Particulate Matter Management in Anyang University funded by the Ministry of Environment and the Korea Environmental Industry & Technology would like to invite you to the “Air quality forecasting using big data and machine learning algorithms” International Conference which will be held at The-K Hotel, Seoul, Korea, on August 24, 2022.

Countries in Northeast Asia including China, Japan, and Korea achieved high economic growth through rapid industrialization and urbanization in recent decades, which resulting in severe pollution problems. Since then, the air quality has been gradually improved through many efforts, but it still falls short of the air quality standards set by the World Health Organization. The significant impact of air pollution on human health is well known, in particular, exposure to PM_2.5 (PM with an aerodynamic diameter of less than 2.5 μm) increases the risk of developing cardiovascular and respiratory diseases. The need for an air quality forecast of PM_2.5 becomes more important as environmental authorities and citizens are requiring air quality information in advance to take appropriate measures and actions to protect their health during pollution episodes.
A lot of research on forecasting and air quality management using machine learning and big data has been actively conducted. According to the research results, it is known that the use of machine learning improves accuracy by reducing the bias in the existing physicochemical model. The objective of this conference focuses on how to build the big data defining the relationship between the source region and the receptor region (i.e., forecast region) reflecting the long-range transport in Northeastern Asia as well as then emphasize on the development the machine learning algorithms such as DNN, RNN, CNN and ensemble modules. The paper presented will be published as the special issues at Asia-Pacific Journal of Atmospheric Sciences (Springer) if the manuscript is submitted until August 31, 2022.