Dela med andra

Real-time characterization of water streams for optimal operation of wastewater treatment plants and sustainable use of resources within circular economy

Publicerad 2020-11-05

Om uppdragsgivaren
Mälardalen University MDH is with 16 000 students one of Sweden’s large Higher Education Institutions. MDH is characterized by close partnerships with industry and the public sector. Engineering research at MDH is particularly strong.

Beskrivning av examensarbetet
Characterization of water streams in energy and environmental systems presents an important challenge. Biomass and waste processing industries as well as wastewater treatment plants show large interest in improving process control and performance optimization to move towards a more environmentally sustainable production.
Contaminants of Emerging Concerns CECs, such as pharmaceutical in the wastewater is of critical importance because of their potentially harmful impacts on environmental resources and exposure to humans and biota. While many of the CECs have been present in the environment for decades, the rising concern is being driven by the importance of analytical techniques that are able to detect them rapidly and at low concentrations. Today, there is a need to establish a protocol for detection of these CECs in the wastewater as well as the sludge. Analysis of CEC in wastewater may be challenging, dealing with various particle sizes, structures, shapes and polymer types dispersed in complex environmental matrices. However, due to the increased presence of CECs in the environment, it is of great importance to start evaluating these analytical techniques.

Proposed tasks:
The proposed project aims to enable real-time characterization of sludge and wastewater properties of interest. The important properties will be identified within the project and may include e.g. elemental composition, energy content, prediction of thermochemical behavior, various CEC concentration in wastewater and sludge, other QA/QC indicators, classification/discrimination of components etc. The near-infrared NIR hyperspectral imaging HSI technology and other optical sensors including Raman, Fourier transform infrared FT-IR and single-point NIR will be coupled with machine learning and artificial intelligence regression and classification algorithms. The second part of the study will evaluate the potentials and limitations of the technology and develop a possible implementation strategy for introduction of such sensors to the complex production systems of wastewater treatment plants WWTPs or elsewhere with overall aim to increase re-use and recycling of waste as well as to improve resource recovery from wastewater and sludge and therefore contributing to the concept of circular economy.

Further information:
The proposed thesis is based on activities planned in ongoing research project funded by VEMM companies: Real-time characterization of material flows for optimal operation of combined heat and powerplants, wastewater treatment plants and waste management facilities and sustainable use of resources within circular economy RENAISSANCE

Jan Skvaril
Högskoleplan 1, 722 20 Västerås

Mälardalens University


Sista ansökningdag

2020, 2021

Project description

Bookmark and Share