Analysis of soil C and O horizon samples in a recent regional geochemical survey of Nord-Tr?ndelag, central Norway (752 sample sites covering 25,000 km2), identified a strong enrichment of several potentially toxic elements (PTEs) in the O horizon. Of 53 elements analysed in both materials, Cd concentrations are, on average, 17 times higher in the O horizon than in the C horizon and other PTEs such as Ag (11-fold), Hg (10-fold), Sb (8-fold), Pb (4-fold) and Sn (2-fold) are all strongly enriched relative to the C horizon. Geochemical maps of the survey area do not reflect an impact from local or distant anthropogenic contamination sources in the data for O horizon soil samples. The higher concentrations of PTEs in the O horizon are the result of the interaction of the underlying geology, the vegetation zone and type, and climatic effects. Based on the general accordance with existing data from earlier surveys in other parts of northern Europe, the presence of a location-independent, superordinate natural trend towards enrichment of these elements in the O horizon relative to the C horizon soil is indicated. The results imply that the O and C horizons of soils are different geochemical entities and that their respective compositions are controlled by different processes. Local mineral soil analyses (or published data for the chemical composition of the average continental crust) cannot be used to provide a geochemical background for surface soil. At the regional scale used here surface soil chemistry is still dominated by natural sources and processes.
This paper addresses the uncertainty associated with release and fire incident rates for trucks in transit carrying dangerous goods. The research extends the treatment of uncertainty beyond sensitivity analysis, low-best-high estimates and confidence intervals, and represents the uncertainty through probability density functions. The analysis uses Monte Carlo simulations to propagate the uncertainty in the input variables through to the resulting release and fire incident rates. The paper illustrates how we can combine information on accident and non-accident releases and fires to generate probability density functions for the total expected releases and fires per billion vehicle kilometres for trucks carrying dangerous goods.