碳中和趋势下数学模拟在污水处理系统中的发展与综合应用

数学模拟技术在污水处理方面被广泛应用,为了系统总结相关技术,本文回顾了污水处理系统中数学模拟技术的发展历程;综述了活性污泥模型(ASM)与机器学习(ML)在水质预测及参数工况优化领域中的应用;重点探究了污水处理系统中温室气体排放模型,以及多目标优化模型在污水处理系统中温室气体排放(GHG)、出水质量(EQI)和运行成本(OCI)的权衡问题;归纳了数学模拟技术在实现污水厂能量自给与资源回收的应用发展.研究结果表明数学模拟技术能准确预测出水水质、快速优化工艺参数、权衡温室气体排放、出水水质与运行成本之间的关系、以及提高资源回收效率等.因此，数值模拟技术可有效指导污水处理工艺的运行优化以及管理,为污水处理行业减污降碳协同增效提供技术支撑.

Development and comprehensive application of mathematical simulation in sewage treatment system under the trend of carbon neutralization

Mathematical simulation technology (MST) has been widely applied in wastewater treatment, therefore, in order to systematically summarize these related technologies, this study reviewed the development of MST in sewage treatment system, and the application of activated sludge model (ASM) and machine learning (ML) in water quality prediction and parameter optimization; In addition, this paper mainly discussed the models of greenhouse gas emission in sewage treatment system, and the trade-off of multi-objective optimization model in sewage treatment system with the objectives of greenhouse gas emission (GHG), effluent quality (EQI) and operating cost (OCI). Furthermore, this paper also summarized the development of MST to achieve the energy self-sufficiency and resource recovery of sewage plant. The results from this study showed that MST can accurately predict the effluent quality, quickly optimize the process parameters, weigh the relationship among greenhouse gas emission, effluent quality and the operation cost, and improve the resource recovery efficiency. Overall, MST can effectively guide the operation optimization and management of sewage treatment process, and ultimately provide technical supports for the synergy of pollution reduction and carbon reduction in sewage treatment industry.