LCT concept – University of Copenhagen

Forward this page to a friend Resize Print Bookmark and Share

Plant and Environmental Sciences > Research > Environmental Chemistry and Physics > Analytical Chemistry > Project: LCT concept

Linking Chemical Fingerprints with Toxicological fingerprints (”the LCT concept”): Can we explain the toxicity of sludge from waste water treatment plants?

Complex mixtures a serious challenge

Assessing toxicity of complex mixtures is a serious challenge. The current methods for risk assessment are based on chemical analyses, toxicological tests and modeling of relatively few target compounds that rarely explains the observed toxicity. In this project, we propose a new concept, the LCT concept, for risk assessment of complex chemical mixtures.

Untargeted approach

In LCT, we will combine advanced chemical fingerprinting of the bioavailable fraction of chemicals with relevant toxicological endpoints. Such an untargeted approach will allow for detection and identification of the main contributors to the toxicity of samples. In contrast to effect directed analysis (EDA), the current state-of-the-art, the LCT concept will also allow detection of combination effects between compounds even with very different physicochemical properties. Sludge from waste water treatment plants applied to agricultural fields as fertilizers will here be used as matrix.

Finding the link by use of newest available techniques

We´ll link the bioavailable chemical fingerprints to the relevant toxicological endpoints using appropriate scaling prior to multivariate regression modeling. LCT combine the newest available untargeted analytical platforms (advanced GC-TOFMS and LC-High-Resolution-MS) with relevant toxicity measures using advanced signal processing and multivariate data analysis for detecting and identifying the major contributors to the chemical toxicity of complex mixtures of organic compounds and metals in environmental samples. Passive equilibrium sample methods of biological relevant fraction of xenobiotics in sludge will be applied to preserve mixture complexity and suitable data processing platforms will be established.

Funded by: The Danish Research Council for Independent Research, Technology and Production Sciences

DKR: 3,720,125

Project period: 1.5.2014 -30.4.2017