Institute for Transuranium Elements
Radioactivity Environmental Monitoring: HOT SPOTS



    The main objective of this research project is to improve environmental reporting techniques relevant to decision-makers by means of methods that can better define the notion of ”hot spots” in a statistical and morphological way.
    Geostatistics is one of the fastest growing fields in environmental sciences. In addition to allowing detailed mapping of environmental variables, it provides scientists and decision-makers with tools for determining local uncertainties and probabilities of exceeding critical thresholds. Nevertheless, many environmental variables (e.g. atmospheric pollutants, epidemics, radioactivity deposition following the Chernobyl accident, precipitation, heavy metals in soils) show spatial patterns with fragmented zones or “patches” with extraordinarily high values, often referred to as hot spots. These hot spots may have greater influence on the assessment of environmental hazards than do the average levels of the variable under study. This problem is illustrated by regular findings in the environment of semi-natural foodstuff that present levels of radioactivity from the Chernobyl accident that largely exceed authorized levels. The detection as well as the mapping of these hot spots remain a challenge for geostatistical techniques. Techniques used in landscape-pattern analysis, in particular for analysing landscape fragmentation, present complementarities with those used in geostatistics. These complementarities need to be defined and could be used to determine a common set of tools for the characterization and identification of hot spots. So far, no such approach to this problem has been explored. In summary, the project aims to:

  1. identify, use and, if needed, develop methods that would allow one to provide useful definitions of "hot spots" (statistically, morphologically, legally) regardless of the environmental variable analysed;
  2. develop and apply methods to analyse and predict spatial distributions of these "hot spots";
  3. develop and apply methods to estimate probabilities to encounter such hot spots.


February 2006-2008.