Real-time forecast of influent flow rate and ammonia in wastewater treatment plant : a case study of Damhusaen catchment in Denmark | |
| Author | Hassan, Zia Ul |
| Call Number | AIT Thesis no.WM-17-09 |
| Subject(s) | Real-time control Ammonia Sewage disposal plants--Denmark |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. WM-17-09 |
| Abstract | Wastewater treatment plants are under pressure to perform better. The rapid expansion in urban population increases the ammonia concentration into urban sewers which become challenging issue throughout the world. In urban areas, main sources of ammonia are human waste, residential lawns and garden, animal waste from farm houses, industrial waste and food waste etc. We have to adopt new rules by modifying how ammonia is measured pursuant to the EPA' s water quality criteria, which provide more accurate protection of aquatic life and better operation of wastewater treatment plan t. With the rapid development of mathematical models, there is possibility to simulate the flow and concentration of ammonia into sewerage system . Catchment runoff and pipe flow are described by MOUSE rainfall runoff and pipe flow modules respectively. Ammonia concentration is described by MOUSE water quality module, advection dispersion equation is used for simulation of ammonia concentration in the sewers. For development of real time control, we use MOUSE control module. This case study is carried out in urban catchment named as Damhusaen catchment Copenhagen, Denmark where there was problem of controlling the ammonia concentration at the inlet point of Damhusaen wastewater treatment plant . According to current operation at the treatment plant, dry and wet weather flow is treated based on average concentration of ammonia which is 40 mg/L and 20 mg/L respectively. The developed methodology helps for determining the ammonia concentration and mass of ammonia at the inlet point of wastewater treatment plan t as a function of forecast lead time, which is six hours. We are able to forecast ammonia concentration six hours before the actual rainfall, it will help for better operation of wastewater treatment plant and increase the efficiency of wastewater treatment plant. The improved measurement information will allow for a reduction of safety factors in the control strategy for protecting the treatment plant and cost effective. One another aim of this study to evaluate accuracies in a flow and ammonia concentration as a function of forecast lead time. From the results, it can be see n that the numerical weather predication model has less accuracy as closer to actual rainfall. So, the predict ion of ammonia concentration is possible with high accuracy six hours before the actual rainfall. Constant and diurnal pattern of ammonia is more sensitive during dry weather flow as compared to wet weather flows. It produces less difference in mass and minimum concentration of ammonia during wet weather flows. Into this study, investigation of the applicability of RTC strategies in the sewer network is done , with the purpose of reducing the overflow into Damhusaen Lake which is located into the Damhusaen catchment. From this approach, there is reduction of the overflow volume o f water and mass of ammonia from the weirs which are discharging into lake. It helps in the reduction of environmental problems into Damhusaen Lake. |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. WM-17-09 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Water Engineering and Management (WM) |
| Chairperson(s) | Babel, Mukand Singh |
| Examination Committee(s) | Duc, Hoang Nguyen;Sutat Weesakul;Mark, Ole |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |