Plósz Benedek Gy, Liltved Helge, Ratnaweera Harsha
Norwegian Institute for Water Research-NIVA, Gaustadalléen 21, NO 0349, Oslo, Norway.
Water Sci Technol. 2009;60(2):533-41. doi: 10.2166/wst.2009.386.
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.
我们对挪威奥斯陆一个在冬季运行时接收合流制下水道系统收集的污水的污水处理系统进行了气候变化影响调查。通过将气象数据与污水数据进行对比得出的结果表明，在该地区确定的每日平均气温临界值约为 -1.5 摄氏度（T(Crit)）以上的临时融雪期，污水处理厂（WWTP）的进水流量显著增加。为了评估融化模式，对高于和低于 T(Crit) 的天数进行了评估，并利用过去十年获得的气象数据额外评估了每年的融化期数量。每日气温模式的一个显著特点是，尽管过去十年冬季气温逐渐升高，但仍可观察到气温低于 -1.5 摄氏度的天数在增加。融化期的频率在冬季有所增加，并且在奥斯陆地区被确定为与气候变化相关的另一个因素。我们证明，这些影响会通过逐渐增加极高进水流量和极低进水污水温度的相对频率而使污水处理厂的运行恶化。这种与气候变化相关的对污水处理过程的影响可被描述为冲击条件，即在相对较短的时间内系统边界条件发生显著变化。在所研究的六年期间，生物脱氮和二次澄清过程显示受到气候因素的显著影响。在决策支持系统中使用最先进的污水处理过程数学模型的一个显著问题是，它们无法描述并因此预测此类冲击负荷事件的影响，因为到目前为止尚未对其进行研究。因此，对过程模型进行调整和优化，使其也能用于设计、优化以及实时自动化和过程控制方案，对于应对未来气候变化的挑战至关重要。
