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Monitoring, understanding, modelling and improving the KAMAK wastewater treatment train

Monitoring, understanding, modelling and improving the KAMAK wastewater treatment train
监控、了解、建模和改进 KAMAK 废水处理系统
批准号:
478745-2015
负责人:
Vanrolleghem, Peter
金额:
$5.75万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31

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英文摘要
The main objective of the proposed research project entitled "Monitoring, understanding, modelling and improving the KAMAK wastewater treatment train" is to increase understanding of the different treatment mechanisms of the KAMAK process. The KAMAK wastewater treatment train, developed by Bionest Technologies Inc., is a solution for enhancing lagoon-based wastewater treatment plants. The train is composed of five distinct zones of which three are clarification zones and two are biofilm reactors. This new technology is important for Canada as lagoon-based processes are the most prevalent technologies for wastewater treatment and a significant fraction of these plants are now overloaded. With a view to achieve this aim, (1) characterizing the removal performances, (2) quantifying the sludge accumulation and degradation in the clarification zones and (3) modeling the key treatment processes of the new technology are the targeted specific objectives. The whole project will be performed on a full-scale KAMAK treatment train. Primodal RSM30 measuring stations equipped with water quality sensors allowing continuous data collection will be used to monitor process performance. Sludge accumulation, a crucial part of lagoon operation, will be quantified as well as the impact of biological activity in the sludge layer on effluent quality. The information gained from the work on the two first objectives will finally be analyzed to develop a mathematical model describing key processes in order to understand and optimize features of the operation of the KAMAK train. The knowledge gained from this project will advance the development of the technology. The results will be used to validate the design criteria and to optimize the components of the KAMAK treatment train.
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