废水处理厂(WWTP)可以受益于利用数字技术减少温室气体(GHG)排放并遵守废水质量标准。在这项研究中,通过改变溶解氧(DO),通过计算机模拟评估了污水处理厂的温室气体排放和电力消耗,混合液再循环(MLR),和回流活性污泥(RAS)参数。三种不同的措施,即,出水水质,温室气体排放,和能源消耗,结合水能碳耦合指数(WECCI)来比较参数对污水处理厂的影响,并确定了最佳操作条件。A2O工艺的初始条件设定为4.0mg/L的DO,100%MLR,和90.7%的RAS。80种不同DO的场景,MLR,并在稳态条件下模拟RAS,优化生物处理工艺。最佳操作条件为1.5mg/LDO,190%MLR,和90.9%的RAS,与初始条件的WECCI(1.07)相比,其WECCI最高为2.40。此最佳条件同时减少了1348kgCO2-eq/d的温室气体排放量和11.64MWh/d的能源消耗。这意味着控制DO,MLR,通过传感器和RAS,阀门,和泵提供了一种有希望的方法来运行污水处理厂,减少电力消耗和温室气体排放,同时达到污水质量标准。此外,一氧化二氮的汽提速率与好氧反应器中的总氨和亚硝酸盐浓度呈线性关系,表明监测废水和反应器中溶解的氮化合物可能是控制生物反应器中MLR和DO的可行策略。本研究开发的基于数字的评估和优化工具有望在更广泛的环境管理工作中应用。
Wastewater treatment plants (WWTPs) can benefit from utilizing digital technologies to reduce greenhouse gas (GHG) emissions and to comply with effluent quality standards. In this study, the GHG emissions and electricity consumption of a WWTP were evaluated via computer simulation by varying the dissolved oxygen (DO), mixed liquor recirculation (MLR), and return activated sludge (RAS) parameters. Three different measures, namely, effluent water quality, GHG emissions, and energy consumption, were combined as water-energy-carbon coupling index (WECCI) to compare the effects of the parameters on WWTPs, and the optimal operating condition was determined. The initial conditions of the A2O process were set to 4.0 mg/L of DO, 100 % MLR, and 90.7 % RAS. Eighty scenarios with various DO, MLR, and RAS were simulated under steady-state condition to optimize the biological treatment process. The optimal operating conditions were found to be 1.5 mg/L of DO, 190 % MLR, and 90.9 % RAS, which had the highest WECCI of 2.40 when compared to the WECCI of the initial condition (1.07). This optimal condition simultaneously reduced GHG emissions by 1348 kg CO2-eq/d and energy consumption by 11.64 MWh/d. This implies that controlling DO, MLR, and RAS through sensors, valves, and pumps offers a promising approach to operating WWTPs with reduced electricity consumption and GHG emissions while attaining effluent quality standards. Additionally, the nitrous oxide stripping rate exhibited linear relationships with the effluent total ammonia and nitrite concentrations in the aerobic reactor, suggesting that monitoring dissolved nitrogen compounds in the effluent and reactor could be a viable strategy to control MLR and DO in the biological reactor. The digital-based assessment and optimization tools developed in this study are expected to hold promise for application in broader environmental management efforts.