Emerging Contaminants Summit

Spring 2020

StudentCompetitionvisanjiZara Visanji
Ph.D. Researcher
University of Exeter

Zara Visanji is a PhD student as part of the Water Informatics Science and Technology CDT at the University of Exeter. She has a BSc in Physical Geography and Geology from the University of Plymouth in 2015 and a MSc in Water Engineering from the University of Exeter in 2017. Her research is an expansion of her masters dissertation based on the removal of emerging pollutants in developing countries. Zara has recently presented her work at the ‘International Conference on Sustainable Development in Civil Engineering’. Her current research interests focus around sustainable treatment technologies for emerging pollutants. She also hopes to develop a decision support tool which will use optimisation techniques and genetic algorithms to determine optimal removal treatment solutions. Zara is also interested in volunteer work, previously she has helped to build a rainwater catchment tank in Fiji and in July 2018 she will be travelling to Uganda to build a spring water well. 

 

POSTER PRESENTATION

A Decision Support Tool for the Fate and Management of Emerging Contaminants in India

This poster introduces a major UK-India collaborative research project funded by the Natural Environment Research Council (NERC) UK and the Department of Science and Technology (DST) India. The aim of the project is to study the fate of emerging contaminants (ECs) in two major Indian rivers, wastewater treatment works and groundwater. The project also includes the development of novel treatment solutions for both rural and urban settings; focussing on the use of advanced oxidation processes assisted by pulsed power treatments, novel graphene based adsorbents and a range of constructed wetlands. The project includes the development of a Decision Support System (DSS) which employs Multi-Objective Optimisation and Multi Criteria Decision Analysis to identify the optimal treatment solutions for the removal of ECs. The DSS has been applied to select optimal solutions for seven different scenarios. Results are presented for the treatment of 39 different types of ECs for 42 different treatment unit processes. 

 

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