Wenbo Ma, Jian Tang, Loai Aljerf, Yongqi Liang, Abdullah H Maad
Municipal solid waste incineration generates by-products like nitrogen oxides, sulfur dioxide, and hydrogen chloride, contributing to environmental issues such as acid rain, ozone depletion, and photochemical smog. While industrial sites use desulfurization and denitrification to reduce emissions, no studies have modeled the formation mechanisms and influencing factors of these pollutants from a pollution reduction perspective. This study first analyzes the municipal solid waste incineration process to identify the main factors affecting the concentration of pollutants related to desulfurization and denitrification. A coupled numerical simulation model for the whole life cycle desulfurization and denitrification process in real municipal solid waste incineration power plants is then constructed using a method that couples two software tools. Next, based on a double orthogonal experimental design, virtual simulation data are generated using the numerical simulation model. Finally, an improved interval type-II fuzzy broad learning algorithm is applied to construct a mechanism model for the whole process of desulfurization and denitrification-related pollutant concentration, using the obtained virtual simulated data. Using a Beijing incineration plant as a case study, the whole life cycle model is successfully established. The research provides data for optimizing pollutant reduction, examines influencing factors, and lays the groundwork for future intelligent control.