UC Irvine

The primary objective of this research is to test the hypothesis that the compounding peaking of process dynamics input and process variables results in much amplified greenhouse gas emissions associated with process power demand in water resource recovery facilities. We developed a simplified equilibrium biokinetic model to study the effects of circadian variations in influent flow and carbonaceous/nitrogenous constituent concentration on the air requirement and the associated energy consumption, energy costs, and carbon emissions. The ultimate goal is to demonstrate the significance of integrating appropriate aeration submodels into the activated sludge model (ASM) family biokinetic models in developing predictive dynamic models for the activated sludge process (ASP).

A model was developed for a water resources recovery facility (WRRF) ASP operating in the Modified Ludzack-Ettinger (MLE) configuration, commonly used for water reclamation. The amplification of air requirements and the associated energy consumption were observed as a result of concurrent circadian variations in ASP influent flow and carbonaceous/nitrogenous constituent concentrations. The indirect carbon emissions associated with the ASP aeration were further amplified due to the simultaneous variations in carbon emissions intensity [kgCO2,eq(kWh)-1] and electricity consumption (kWh). The ratio of peak to minimum increased to 3.4 (for flow), 4.2 (for air flow and energy consumption), and 5.2 (for indirect CO2,eq emission), which is indicative of strong amplification. Similarly, the energy costs for ASP aeration were further increased due to the concurrency of peak energy consumption and power demand with time-of-use (TOU) electricity rates. A comparison between the results of the equilibrium model and observed data from the benchmark WRRF demonstrated the occurrence of under- and over-aeration attributed to the circadian variation in air requirements and limitations associated with the aeration system specification and design. Our results not only test the research hypothesis but offer practical recommendations for operations and design/retrofit.