2010 Meeting at EGU General Assembly
Vienna, Austria, 2 - 7 May 2010
Session NH8.3: Radon, Health and Natural Hazards.
This session focused on a variety of impacts and hazard-associated manifestations of radon gas and was a development of the EGU 2009 meeting, with focus specifically on a recently established IGCP Project 571. Radon has a major significance for human health as the second leading cause of lung cancer. As well as being a hazard in its own right, there is evidence that radon concentrations (for example, atmospheric, soil-gas and groundwater) can be used as a diagnostic of crustal geophysical processes and, hence, associated geohazards. For example, recent researches have revealed radon anomalies observed as possible earthquake precursors. A link has also been demonstrated between ocean and earth tides and built-environment radon levels in some locations. Due to radon emanating from rocks and soils, there are also archaeological aspects which include links between (ancient) mines and the health of miners, cave dwellers (historical and modern), cave visitors / guides and archaeological excavations/ excavators. This session will present a broad range of papers including methodological, technological and interpretative aspects, as well as case study material.
Session SC3/NH11.1: An Introduction to Time-Series Analysis for the Investigation of Natural Hazards.
The aim of this short-course was to provide an introduction to and overview of key techniques of time-series analysis to identify and quantify - and perhaps predict - natural hazards. It took key questions such as 'Are we looking for cyclic or anomalous phenomena?' as its starting point: time-series analysis can be used to identify both cyclic and temporally anomalous events.
Many natural hazards have cyclic/periodic features; these include radon, earthquakes (under some circumstances), (seasonal) droughts and floods, whereas others are anomalous, apparently random with regard to time, such as earthquakes (under most circumstances). For the cyclic cases, an analysis of past time-series can yield an expectation and perhaps some degree of forecasting, even if only at the level of 'more probable' and 'less probable' times. For anomalous events, investigation of past time-series might reveal evidence of precursory events which again might permit some degree of forecasting, even if only at the level of 'more probable' and 'less probable' times.
The focus was on key Fourier and related techniques such as Fourier transforms and auto- and cross- correlation. Anticipating that most of those who attended were 'users' rather than 'developers', emphasis was given to the interpretation of the output.