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Non-Target Screening for Environmental Samples
Provider: Faculty of Science

Activity no.: 5745-24-09-31 
Enrollment deadline: 19/04/2024
PlaceDepartment of Plant and Environmental Sciences
Date and timeApril 2024 - June 2024
Regular seats25
Activity Prices:
  - Participant10,000.00 kr.
  - Deltager/Participant Others15,000.00 kr.
LecturersJan H. Christensen
Selina Kornelia Tisler
ECTS credits7.50
Contact personSelina Kornelia Tisler    E-mail address: seti@plen.ku.dk
Enrolment Handling/Course OrganiserJan H. Christensen    E-mail address: jch@plen.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 4
Scheme group note22.april - 23. juni 2024 (Tuesdays, Thursdays)
Exam requirementsHanding of a report and attend oral examination. group presentation about the project and questioning individual with internal censor. The questioning will be about the content of the entire course and the project
Course workload
Course workload categoryHours
Theoretical exercises30.00
Lectures30.00
Field Work25.00
Examination21.00
Preparation100.00
Colloquia0.00
Sum206.00
Aim and content
The aim of the course is to introduce participants to the use of suspect screening (SS) and non-target screening (NTS) analysis of environmental samples. The course provides an overview and hands-on experience of different NTS strategies. These strategies are tools to identify unknown molecules and evaluate their relevance and fate in the environment. The course focuses on NTS with different chromatographic techniques and different environmental matrices. The course structure will be a combination of lectures and theoretical exercises, to apply the learned tools continuously combined with a practical NTS project in the last three weeks of the course.

Lectures will include introductory lectures on NTS, analytical workflows, peak detection, and identification and quantification workflows using open software solutions. The lectures will be centered on liquid chromatography – high resolution mass spectrometry (LC-HRMS) and waste-, surface-, and drinking water samples, but other matrices (e.g., soil, sediment, urine), and chromatographic platforms such as gas chromatography - GC, supercritical fluid chromatography - SFC, multidimensional chromatography GC, LC and SFC, and ion mobility spectroscopy (IMS) will also be covered.
The practical work will consist of a three-week project where the participants will follow one sample and include all parts from sample preparation to the final peak identification and quantification of chemicals of emerging concern in selected water samples. The work will include solid phase extraction (SPE), vacuum evaporation up-concentration (VEC), analysis with LC or SFC, peak detection using selected open software solutions such as MSDial and MZmine, data filtering, compound prioritization (R scripts) and suspect screening (SS) (with suspect libraries).

Formal requirements

As prerequisite a course in instrumental analysis, like the course "Analytical Chemistry", is strongly recommended, since all basic theory of separation, chromatographic instruments and mass spectrometry is assumed to be known.

Registration with application (motivational letter):
Please write an email to course organizer Selina Kornelia Tisler beforehand (seti@plen.ku.dk), including a short description of your background and motivation for the course

 

Learning outcome
Knowledge:
The students will obtain knowledge on:
-the definitions of suspect- and non-target screening (SS and NTS) and the strengths and weaknesses of different workflows used to answer environmental questions.
-basic concepts of SS and NTS including sample preparation, data acquisition, quality controls, data processing, data filtering, prioritization and interpretation.
-Quality controls of SS and NTS data

Skills:
The student will be able to
-plan NTS workflows based on specific research question (sample preparation, data acquiring, data processing and analysis)
-conduct data processing of NTS data to prioritize features and identify unknowns
-assess, quantify and correct for variations and drift in the data (quality control for NTS)
-interpret high resolution mass spectrometer data to identify chemicals without available analytical standards
-use SS and NTS based on open-source software solutions

Competences:
The course enables the student to plan and conduct a NTS study. The student will be able to choose the right analytical platform and to investigate environmental samples with NTS. The student will also be able to critically assess and interpret the data.

Literature
Course manual (distributed before the start of the course)
NORMAN guidance on suspect and non-target screening in environmental monitoring, Hollender J. et al (2023), https://doi.org/10.1186/s12302-023-00779-4

Target group
The course is aiming for participants with knowledge in analytical chemistry. The background can be from different research fields: e.g. food, medical and health science, environment, biotechnology.

Teaching and learning methods
Lectures, expert lectures, theoretical exercises on NTS workflows, hands-on NTS workflow conducted in the laboratory as group work.

Project work:
The project work will be performed at the laboratories at University of Copenhagen, Frederiksberg Campus. Participants will up-concentrate their samples (SPE or VEC), analyze them (e.g. LC or SFC) and process the data via NTS workflows to prioritize compounds in water samples (e.g. groundwater, wastewater). Finally, selected contaminants of emerging concerns will be tentatively identified and semi-quantified.

Lecturers
Assistant Professor Selina Tisler,
Professor Jan H. Christensen,
Associate Professor Giorgio Tomasi

Remarks

Course fee:
For participants from Danish Universities teaching is free of charge. External students are charged 5.000 DKK for the teaching in addition to the running costs.
All PhD students (including those from Danish Universities) are charged for instrument-time and laboratory expenses amounting to a total of 10.000 DKK for the full course (7.5 ECTS).

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University of Copenhagen discloses non-sensitive personal data to course leader/speakers, if any. In addition, we will disclose non-sensitive personal data to the other participants in the course. Non-sensitive personal data includes names, job positions, institution names & addresses, telephone numbers and e-mail addresses.

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