modelEAU, Département de génie civil et de génie des eaux, Université Laval, 1065 Avenue de la Médecine, Québec, Quebec, Canada.
Biotechnol Bioeng. 2012 Nov;109(11):2854-63. doi: 10.1002/bit.24544. Epub 2012 May 19.
New tools are being developed to estimate greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs). There is a trend to move from empirical factors to simple comprehensive and more complex process-based models. Thus, the main objective of this study is to demonstrate the importance of using process-based dynamic models to better evaluate GHG emissions. This is tackled by defining a virtual case study based on the whole plant Benchmark Simulation Model Platform No. 2 (BSM2) and estimating GHG emissions using two approaches: (1) a combination of simple comprehensive models based on empirical assumptions and (2) a more sophisticated approach, which describes the mechanistic production of nitrous oxide (N(2) O) in the biological reactor (ASMN) and the generation of carbon dioxide (CO(2) ) and methane (CH(4) ) from the Anaerobic Digestion Model 1 (ADM1). Models already presented in literature are used, but modifications compared to the previously published ASMN model have been made. Also model interfaces between the ASMN and the ADM1 models have been developed. The results show that the use of the different approaches leads to significant differences in the N(2) O emissions (a factor of 3) but not in the CH(4) emissions (about 4%). Estimations of GHG emissions are also compared for steady-state and dynamic simulations. Averaged values for GHG emissions obtained with steady-state and dynamic simulations are rather similar. However, when looking at the dynamics of N(2) O emissions, large variability (3-6 ton CO(2) e day(-1) ) is observed due to changes in the influent wastewater C/N ratio and temperature which would not be captured by a steady-state analysis (4.4 ton CO(2) e day(-1) ). Finally, this study also shows the effect of changing the anaerobic digestion volume on the total GHG emissions. Decreasing the anaerobic digester volume resulted in a slight reduction in CH(4) emissions (about 5%), but significantly decreased N(2) O emissions in the water line (by 14%).
正在开发新的工具来估算废水处理厂（WWTP）的温室气体（GHG）排放量。目前的趋势是从经验因素转向简单综合和更复杂的基于过程的模型。因此，本研究的主要目的是展示使用基于过程的动态模型来更好地评估 GHG 排放的重要性。这是通过定义基于整个工厂的基准模拟模型平台 2（BSM2）的虚拟案例研究来实现的，并使用两种方法估算 GHG 排放：（1）基于经验假设的简单综合模型的组合，以及（2）一种更复杂的方法，该方法描述了生物反应器（ASMN）中氧化亚氮（N2O）的产生机制以及厌氧消化模型 1（ADM1）中二氧化碳（CO2）和甲烷（CH4）的产生。使用已经在文献中提出的模型，但对以前发表的 ASMN 模型进行了修改。还开发了 ASMN 和 ADM1 模型之间的模型接口。结果表明，不同方法的使用导致 N2O 排放的显著差异（3 倍），但 CH4排放的差异不大（约 4%）。还比较了稳态和动态模拟的 GHG 排放估算。稳态和动态模拟得到的 GHG 排放平均值相当相似。然而，当观察 N2O 排放的动态时，由于进水废水 C/N 比和温度的变化，观察到很大的可变性（3-6 吨 CO2e/天），这将不会被稳态分析所捕获（4.4 吨 CO2e/天）。最后，本研究还表明了改变厌氧消化体积对总 GHG 排放的影响。减小厌氧消化池体积导致 CH4排放略有减少（约 5%），但在水线中显著减少了 N2O 排放（减少 14%）。
