Applying a Seasonal Adjustment Method to Continuous Dissolved Nitrous Oxide Data in a Carrousel Reactor

Abstract

The aim of this study was to extract medium-term nitrous oxide (N₂O) fluctuations, that is fluctuations over time scales of several days, from continuous data in a biological reactor. Although N₂O emission may fluctuate over the medium-term, a large short-term fluctuation made it difficult to observe. We analyzed approximately one month of continuous dissolved N₂O data in a Carrousel reactor for sewage water in 2019. After confirming the characteristics of the data, we applied a seasonal-trend decomposition procedure with loess: STL decomposition, which is one of the nonparametric seasonal adjustment methods. As a result, medium-term fluctuations of dissolved N₂O concentrations were observed as time-series data eliminating short-term diurnal fluctuations. Furthermore, a characteristic peak of the medium-term fluctuation was explained by the fluctuation of the influent volume depending on the immediately preceding rainfall. Therefore, it is necessary to consider the effect of rainfall for a statistical model of nitrous oxide production.