## 3 Discussion  
Based on the process data analyzed for the ABAC system currently installed at the IEUA RP-1 facility, it is recommended to continue monitoring the energy consumption of the unit to obtain at least a full year of data (i.e., August 2019 through August 2020). The data must be normalized to influent contaminant loading as well as air transfer ratio, as these factors have been shown to impact energy consumption the most. With the four months analyzed as part of this study (August through December 2019), the ABAC system is demonstrating energy consumption savings of approximately 9% and the three months of 2020 data collected demonstrate promising trends for a continued savings. Additionally, trends of system ammonia loading, DO set point and readings as well as the improvements in bleach dosage demonstrate the ABAC units are working appropriately. IEUA senior operation staff members have supported the use of the ABAC system as it provides a reliable tool to mitigate high ammonia loading episodes. Limitations to this study include the use of less than one year of process data to determine trends; as more data are collected with the ABAC unit in service, the accuracy of the cost savings analysis is expected to increase. The ABAC system installed in IEUA RP-1 facility has been successfully proven to reduce energy consumption costs for facility operation as expected from by the ABAC application theory. The control system and equipment that make up the ABAC system have the capability to accurately set the appropriate DO level based on incoming ammonia loading and consequently reach the corresponding DO concentrations in the aeration basins through control of the air supply. As suggested by the preliminary date, the overall use of bleach in the facility has shown a reduction but whether it can be fully attributed to the ABAC system is yet to be further investigated. In addition to the cost savings demonstrated, the real-time ammonia loading data supplied by the ABAC system have given RP-1 operators improved control and optimization opportunities for the process. This improvement in control has increased treatment efficiency and long-term operation strategy. The results of study therefore warrant further investigation of energy consumption and chemical usage reductions in large-scale wastewater treatment application. Moreover, this study provides a framework for the analysis of data collected from an ABAC system to appropriately consider system factors. [PERSON] and [PERSON] presented the idea and together designed the data-gathering approach. [PERSON] processed the data and wrote the original manuscript. [PERSON] reviewed the data and provided input for data normalization. [PERSON] contributed institutional knowledge of the facility and created the air transfer ratio equation. [PERSON], [PERSON], [PERSON] ([PERSON]), [PERSON], and [PERSON] reviewed and edited the manuscript and made key contributions to the background and discussion sections. [PERSON]. ([PERSON]) reviewed the manuscript and supported funding for the APC. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The APC was funded by the Inland Empire Utilities Agency. Authors acknowledge the collaboration and technical support of the Inland Empire Utilities Agency, specifically [PERSON], the RP-1 Operations Team and the Engineering & Construction Management Department. The authors declare no conflict of interest. Calculation Appendix A: Correlation of Contaminant Loading and Air Flow Rates  
Equation (A1):  
\[\text{Correlation }(\text{X},\text{Y})\ =\ \frac{n\ (\sum\ xy)-(\sum\ x)(\sum\ y)}{ \sqrt{\left[n\sum\ x^{2}-(\sum\ x)^{2}\right]\left[n\sum\ y^{2}\ -(\sum\ y)^{2}\right]}}\] (A1)  
where X and Y are the calculated means for the data sets and n is the sample size. In this case, X is Average Daily Air Flow (SCFH) and Y is the contaminant loading (lb/day).