A source classification framework supporting pollutant source mapping, pollutant release prediction, transport and load forecasting, and source control planning for urban environments
Related Experiment Video
Updated: May 28, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Hans-Christian Holten Lützhøft1, Erica Donner, Tonie Wickman
1Department of Environmental Engineering, Technical University of Denmark, Miljoevej 113, DK-2800, Kgs. Lyngby, Denmark. hhlu@env.dtu.dk
Purpose:
Implementation of current European environmental legislation such as the Water Framework Directive requires access to comprehensive, well-structured pollutant source and release inventories. The aim of this work was to develop a Source Classification Framework (SCF) ideally suited for this purpose.
Methods:
Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe.
Results:
The SCF is structured in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority pollutant release data.
Conclusions:
The SCF provides a well-structured approach for European pollutant source and release classification and management. With further optimisation and demonstration testing, the SCF has the potential to be fully implemented throughout Europe.
More Related Videos
09:44Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
Published on: October 16, 2018
05:47In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Related Concept Videos
GIS Software, Hardware, and Sources of GIS Data
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Manipulation and Analysis
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
Levels of Use of a GIS
Selected Data About Geographic Locations