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Research was undertaken to determine the potential for changes in GHG emissions based on the magnitude of aeration, as enhanced by the need for mixing and shearing biofilm (to manage the biofilm thickness), the type of media (fixed bed versus moving bed), and the location of media in IFAS systems. The information was used to verify the biofilm and IFAS components of the Aquifas + simulator. The simulator was developed with a proprietary algorithm that can achieve speeds greater than 100 times that of other commercial biofilm models, while solving twice as many equations for the biofilm to accommodate GHG simulations. The proprietary elements of the algorithm modify the Newton Raphson method for solving equations and the Euler method for row reduction during matrix inversion in a manner that achieves substantially higher speeds and computational accuracy. The nitrification and denitrification reactions are broken up into four steps each to simulate nitrous oxide, nitric oxide, nitrite and nitrate forms of nitrogen. The oxidized nitrogen products with reactions where both ordinary heterotrophs (OHO), polyphosphate accumulating organisms (PAO) can consume them. This expanded the activated sludge component of IWA-ASM2d from 19 to 54 equations, and the biofilm component from 19 to 34 equations.As part of this research, it was determined that an IFAS system could denitrify better with the biofilm added to the anoxic cell, and the denitrification flux (oxidized-N reduction inside biofilms, especially in thicker biofilms) creates a lower potential for emitting GHG as nitrous oxides in the anoxic zone. The simulator was applied to evaluate and conclude that the higher buffer on air supply in IFAS that is created when the aeration requirements have to satisfy the need for media mixing to shear the biofilm helps achieve more complete nitrification, thereby lowering the potential for GHG emissions. Dynamic simulation with the higher aeration and mixing shows that the more complete nitrification that can be achieved with the additional air and media in a properly designed IFAS system can also reduce the emission of nitrous oxides from the aerobic zone during peak flow periods.

An Artificial Intelligence system was developed and implemented for water, wastewater, and reuse plants to improve management of sensors, short and long-term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it can simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.