ANN-based prediction of ammonia nitrogen for wastewater discharge indicators under carbon neutral trend - Liu, Hongbo; Jian, Haoran (Frontiers in Ecology and Evolution, 2023)
With the rapid development of society and the acceleration of urbanization, human activities have led to an increasing amount of greenhouse gas emissions, resulting in a series of ecological and environmental problems such as global warming. The sharp increase in urban water consumption has also correspondingly increased sewage discharge, exacerbating the shortage of freshwater resources and water environmental pollution. Ammonia nitrogen is an important indicator of water pollution, and excessive levels can cause eutrophication and environmental pollution in water bodies. Therefore, understanding the current status and spatial distribution characteristics of greenhouse gas emissions in China's sewage treatment industry is of great significance for formulating emission reduction measures, controlling ammonia nitrogen emissions from sewage treatment plants, and achieving the goals of "carbon peak" and "carbon neutrality". This article comprehensively studies the current status and influencing factors of greenhouse gas emissions from sewage treatment plants, predicts the future spatial and temporal distribution characteristics of emissions, and considers emission factors and technological innovations that are suitable for China's national conditions. The uncertainty of ammonia nitrogen emissions from sewage treatment plants is calculated using the analysis error propagation method of the IPCC, which includes the uncertainty range of individual variables and the total uncertainty result. Additionally, an artificial neural network is used to predict the ammonia nitrogen content in sewage discharge to prevent the occurrence of excessive ammonia nitrogen content in the discharged wastewater.