AI Article Synopsis
- The study focused on mapping metal concentrations in mosses across eight European countries during the years 1990, 1995, and 2000, using geostatistics to analyze the data.
- Results showed significant local variability and patterns, with differences in metal levels detected on either side of national borders, though inconsistencies arose from using various laboratory techniques for analysis.
- An example from German moss data illustrated that factors such as moss species, local pollution sources, and environmental conditions like rainfall primarily influenced metal concentration variations.
Article Abstract
This study aimed at cross-border mapping metal loads in mosses in eight European countries in 1990, 1995, and 2000 and at investigating confounding factors. Geostatistics was used for mapping, indicating high local variances but clear spatial autocorrelations. Inference statistics identified differences of metal concentrations in mosses on both sides of the national borders. However, geostatistical analyses did not ascertain discontinuities of metal concentrations in mosses at national borders due to sample analysis in different laboratories applying a range of analytical techniques. Applying Classification and Regression Trees (CART) to the German moss data as an example, the local variation in metal concentrations in mosses were proved to depend mostly on different moss species, potential local emission sources, canopy drip and precipitation.
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| http://dx.doi.org/10.1016/j.envpol.2007.06.025 | DOI Listing |
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