[WATER] Optimising biological nutrient removal processes in a future of low carbon and low cost in the water industry

Lead Research Organisation: Cranfield University
Department Name: Sch of Energy, Environment and Agrifood


The water industry is increasingly under pressure to achieve high standards of treated waste water discharges in particular in relation to nutrients, minimising carbon footprint, and at the same time, minimising capital and operational costs. This generates a new and challenging framework for waste water treatment technology optimisation to achieve, not only compliance, process robustness and resilience but also to reduce associated carbon and economic costs. Therefore, the water industry need new approaches to provide solutions for environmental and health protection. This programme examines new biological modelling approaches for a fixed film process (rotating biological contactor - RBC) which is one of the most prominent low energy technologies used at thousands of small scale treatment works in the UK. The purpose of this work is to explore the underlying mechanisms that influence and limit RBC performance through the development and application of a new approach to biological fixed film models for nutrient removal. Engineering aspects such as rotation speed, aeartion and media type are known to affect pollutant removal by the biofim. Recent advances in the understanding of biofilm development, nitrification process requirements, potential effects of rotational speed (Di Palma and Verdone 2009), and attempts to model oxygen transfer (Kubsad et al. 2004, Chavan and Mukherji 2008) provide a new opportunity for optimising and rationalising biofim modelling and thus RBC design and operation. The work programme will include a critical review of past approaches to RBC optimization and biofilm development models. In addition, data mining will be conducted on Severn Trent's records to characterise the robustness and resilience of the process. The project partner has over 350 small sewage works which have employed RBCs for secondary treatment of domestic waste waters throughout the past 20 years. Experimental trials will be conducted to validate the modelling approach. The project has a significant impact in the training of the researchers of the future. The doctoral student will be embedded within the water industry on a leading-edge research topic. The studnet will attend the Schools Research Training Programme (http://www.cranfield.ac.uk/soe/esrstp/) and so develop research investigation and communication skills. In addition technical training will be achieved through the completion of taught MSc models in the Centre for Water Science this will enable the researcher to possess expert knowledge in their specialist field of biological processes and also be able to deploy methods and techniques that balance social, environmental, economic, and engineering considerations. Whilst completing their research programme at Severn Trent they will receive business training relating to effective project management and will become familiar with business processes and client needs. The results from this work will provide a better understanding of a robust, low energy technology for achieving increasingly tighter demands for environmental and health protection, thus contributing both to the scientific understanding of processes within the reactors and informing the design of the technological application within the water industry. The project will necessarily entail the implementation of research methods from various disciplines, such as process engineering and environmental science among others, to deliver a biofim model and thus improved RBC operation and design that is robust not only in terms of treatment performance but is also embedding the importance of carbon footprint in waste water treatment process optimisation. The impact of this work will be to deliver a new modelling approach for biological fixed film processes which can be applied to thousands of sites to optimise pollutant removal at the lowest carbon cost.


10 25 50