Identifying factors that correlate with Enhanced Biological Phosphorus Removal upsets at Lundåkraverket

Abstract: The Enhanced Biological Phosphorus Removal (EBPR) process is characterized as the most sustainable process to remove phosphorus from wastewater albeit with high variability in performance efficiency. Thus, unpredictable upsets in the EBPR system is the norm across several wastewater treatment plants throughout Sweden, forcing the hand of the operators to dose higher volume of chemicals to reach the effluent requirements. As future effluent requirements are getting stricter and since higher chemical usage is environmentally and economically unsustainable, this investigation was setup to evaluate which environmental, operational and/or wastewater characteristics correlate with EBPR upsets at full-scale wastewater treatment plant (WWTP), more specifically at Lundåkra WWTP operated by Nordvästra Skånes Vatten och Avlopp (NSVA). The data used in the investigation was collected between 1St January 2018 and 31St December 2020 for a vast number of parameters known to play a key role in biological phosphorus removal. Online sensors as well as external and internal analysis contributed to the data which included parameters such as ‘Total flow at the plant’, ‘pH of the incoming water’, ‘Temperature in aeration basins’, ‘Dissolved oxygen (DO) levels in aeration basins’, ‘Nitrate in aeration basins’, ‘Sludge content in aeration basins’, etc. Other relevant parameters such as ‘Hydraulic retention time (HRT) in the treatment units’, ‘Sludge retention time (SRT) in aeration basin’, ‘Organic loading rate (OLR)’, etc. were calculated. Before the start of this investigation, the two possible explanations were presumed and they can be classified as: (i) upsets as a result of unsuitable environmental conditions and/or error in the operational strategy at the plant and (ii) upsets as a result of toxicity from higher concentration of metals in the influent specifically. Traditional statistical methods such as the t-distributed Stochastic Neighbor Embedding (t-SNE), Spearman Rank Correlation and Principal Component Analysis were used for the purpose of this study to test the first presumed explanation. The t-SNE plot showed that the upsets did not cluster into one large group but instead clamped up into smaller groups scattered across the length of the scale in both dimensions. This points towards the multivariate dependency of the EBPR process and exhibits that upsets might occur even with an operational strategy that produces good results otherwise. This, in turn, eludes to the fact that a non-included parameter such as the ‘daily metal concentrations in the influent’ could be responsible for some or all of the upsets. The Principal Component Analysis (PCA) plot, although noisy, offered an improvement strategy built around the key variables namely ‘nitrate in aeration basin 1 & 2’, ‘sludge content in aeration basin’, ‘SRT in aeration basin’, ‘O2 in aeration basin 1 & 2’ and ‘pH of incoming water’. Therefore, it is recommended that an improvement strategy be devised around them. Multiple causal factors increase the complexity of the analysis by decreasing the correlation coefficients, however, incorporation of the scatterplots presents a clearer picture. The parameters ‘nitrate in aeration basin 1 & 2’ and ‘sludge content in aeration basin’ showed the strongest correlation with phosphate values at the end of biological treatment at -0.32 and 0.42 respectively. The results also open the door to future research and provide direction for further investigations.