Statistical Characterization of Full-Scale Thermophilic Biological Systems to Inform Process Optimization

This paper focuses on using a novel approach to assess the statistical variability of management data from an aerobic thermophilic biological plant (AWTP) utilizing a fluidized bed biological reactor. A proper statistical characterization of full-scale thermophilic biological systems, in fact, may inform process optimization in the light of a future automation of treatment plants. We present a case study that spans the period from 2018 to 2023 and encompasses various high-strength aqueous waste (AW) in continuous mode. Key aspects of the proposed analytical approach include: (i) utilizing advanced descriptive statistics, such as violin graphs, to depict the variability of monitored parameters over five years; (ii) conducting correlation analyses (Spearman and Pearson correlation matrices) specifically focusing on nitrogenous forms within the AW; (iii) applying multivariate statistical analysis to assess the correlation between pollutants released and the plant's energy and oxygen consumption; and (iv) reconstructing parameter trends by considering periodic and random components, thus enhancing the understanding of the system's behavior over time. The findings presented in this paper offer valuable insights into the performance and optimization of AWTPs, potentially leading to a proper planning of the loads and consequent feeding of the plants. If properly enacted, our approach may provide a significant contribution to the field of aqueous waste management.