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Geostatistical Investigation of forest soil contamination from Mining and Smelting Activities in Goslar District (Middle Germany)

مؤلف البحث
Ragab Rabeiy, Wolfgang Busch, Steffen Knospe, and Walter Schmotz
المشارك في البحث
سنة البحث
2010
مجلة البحث
5th Annual International Symposium on Environment
20-23 of May 2010, Athens, Greece
الناشر
First Published in Athens, Greece by the Athens Institute for Education and Research
عدد البحث
NULL
تصنيف البحث
3
صفحات البحث
24
موقع البحث
NULL
ملخص البحث

Goslar district in Lower-Saxony, Germany, was one of the most important mining and metal production areas in the world. The long time of mining, mineral processing and smelting activities in the area have enriched the forest soil with many heavy metals. Spatial distribution of soil heavy metals Pb, Zn, and As was investigated using geostatistical methods and geographic information system (GIS). Geostatistical Analyst extension of ArcGIS was used to explore the raw data, transform to normality and calculate the experimental variogram and its fitted model. Ordinary Kriging was applied to predict the spatial distribution of soil heavy metals. A GIS model was built to optimize the spatial distribution of heavy metals by selecting new soil samples in sites of maximum Standard Prediction Error. Comparison between predicted surfaces before and after taking the new samples was studied. Hotspot locations of polluted soil were investigated by creating specific geostatistical structures for each intensive contaminated site. These specific predicted surfaces of hotspot locations are merged into the general predicted surface of the same soil heavy metal.