Towards an Autonomous Algal Turf Scrubber: Development of an Ecologically-Engineered Technoecosystem

Abstract

The development of an autonomous and internally-controlled technoecological hybrid is explored. The technoecosystem is based on an algal turf scrubber (ATS) system that combines engineered feedback control programming with internal feedback patterns within the ecosystem. An ATS is an engineered, high-turbulent aquatic system to cultivate benthic filamentous algae for the removal of pollutants from an overlying water stream. This research focuses on designing a feedback control system to control the primary production of algae in an ATS through monitoring of the algal turf metabolism and manipulation of the turbulence regime experienced by the algae. The primary production of algae in an ATS, and thus the potential of the waste treatment process, is known to be directly related to the level of turbulence in the flowing water stream resulting from the amplitude and frequency of the wave surge. Experiments are performed to understand the influence of turbulence on the biomass production rate of algae in an ATS. These results show that biomass production is correlated with wave surge amplitude at a constant frequency. Further, the influence of turbulence on the net ecosystem metabolism of an algal turf in an ATS was investigated. Results showed that both net primary production and respiration, measured through the diurnal change of inorganic carbon, follow a subsidy-stress relationship with increasing wave surge frequency, although some of this trend may be explained by the transfer of metabolic gases across the air-water interface. A feedback control algorithm, developed to monitor the net primary production and manipulate a controlling parameter, was found to converge quickly on the state of maximum primary production when the variance of the input data was low, but the convergence rate was slow at only moderate levels of input variance. The elements were assembled into a physical system in which the feedback control algorithm manipulated the turbulence of the flow in an ATS system in response to measured shifts in ecosystem metabolism. Results from this testing show that the system can converge on the maximum algal productivity at the lowest level of turbulence--the most efficient state from an engineering perspective--but in practice the system was often confounded by measurement noise. Investigation into the species composition of the dominant algae showed shifting relative abundance for those units under automated control, suggesting that certain species are more suited for utilizing the technological feedback pathways for manipulating the energy signature of their environment.