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Greenhouse Gas Emissions from Wastewater Treatment Plants on a Plantwide Scale: Sensitivity and Uncertainty Analysis

机译:全厂范围内废水处理厂的温室气体排放:敏感性和不确定性分析

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This paper presents the sensitivity and uncertainty analysis of a mathematical model for greenhouse gas emission (GHG) and energy consumption assessment in wastewater treatment plants. A sensitivity analysis was carried out (using two different methods) to determine which model factors have the greatest effect on the predicted values of the GHG production. Further, an uncertainty analysis was carried out to quantify the uncertainty of the key model outputs, such as carbon dioxide production from activated sludge treatment. The results show that influent fractionation factors, which characterize influent composition, have an important role on direct and indirect GHGs production and emission. Moreover, model factors related to the aerobic biomass growth show a relevant influence on GHGs in terms of emission from off-site power generation (m(CO2eq;PG)). Further, model factors related to the autotrophic biomass growth were found to strongly interact with other factors especially in modeling m(CO2eq; PG). Finally, nitrous oxide (N2O) emission associated with the effluent has the highest uncertainty, suggesting the need for a mechanistic model for N2O production in biological treatment. (C) 2016 American Society of Civil Engineers.
机译:本文介绍了废水处理厂温室气体排放(GHG)和能耗评估数学模型的敏感性和不确定性分析。进行了敏感性分析(使用两种不同的方法),以确定哪些模型因素对温室气体产量的预测值影响最大。此外,还进行了不确定性分析以量化关键模型输出的不确定性,例如活性污泥处理产生的二氧化碳。结果表明,影响进水成分的进水分馏因子对直接和间接温室气体的产生和排放具有重要作用。此外,与好氧生物量增长相关的模型因素在场外发电的排放量(m(CO2eq; PG))方面显示出对温室气体的相关影响。此外,发现与自养生物量增长有关的模型因子与其他因子强烈相互作用,尤其是在建模m(CO2eq; PG)时。最后,与废水相关的一氧化二氮(N2O)排放具有最高的不确定性,这表明在生物处理中需要一种用于生产N2O的机理模型。 (C)2016年美国土木工程师学会。

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