Climate change impacts on activated sludge wastewater treatment: a case study from Norway

We present an investigation on climate change effects on a wastewater treatment system that receive sewage collected in a combined sewer system in Oslo, Norway, during winter operation. Results obtained, by contrasting meteorological data with sewage data, show that wastewater treatment plant (WWTP) influent flow rates are significantly increased during temporary snow melting periods above a critical daily air mean temperature of approx. -1.5 degrees C degree (T(Crit)) identified in the area. In order to assess melting patterns, the number of days above and below T(Crit) was assessed, and the annual number of melting periods was additionally evaluated using meteorological data obtained in the last decade. A striking thing about the daily air temperature pattern is that, despite the progressively warmer winter temperatures in the last decade, an increasing number of days with temperatures below -1.5 degrees C could be observed. The frequency of melting periods is shown to increase in wintertime, and it is identified as an additional climate change related factor in the Oslo region. We demonstrate that these impacts can deteriorate the WWTP operation through progressively increasing the relative frequencies of very high influent flow rate and of the very low influent sewage temperature. Such climate change related effects on sewage treatment processes can be characterised as shock-conditions, i.e. significant changes in a system's boundary conditions, occurring in a relatively short period of time. In the six year period examined, biological nitrogen removal and secondary clarification processes are shown to be significantly affected by the climate factors. A striking thing about using the state-of-the-art mathematical models of wastewater treatment processes in decision support systems is their inability of describing, and thus predicting the effects of such shock-loading events, as they have not been studied so far. Adaptation and optimisation of process models, also for use in design, optimisation as well as in real-time automation and process control schemes, are thus critical to meet the challenges of climatic changes in the future.