engleski

Mapping soil pollution by heavy-metals using continuous limitation scores

The paper demonstrates methodology to assess overall soil pollution 8 in a sampled area by using continuous limitation scores. The interpolated heavy 9 metal concentrations are first transformed to negative limitation scores using the 10 exponential transfer function determined by using two threshold values: marginally 11 polluted soil (1 limitation point) and critically polluted soil (5 limitation point). The 12 limitation scores can then be summed to produce the map of cumulative limitation 13 scores. The methodology was illustrated using the 784 soil samples of Cd, Cr, Cu, 14 Ni, Pb and Zn in central region of Croatia. The heavy metals were sampled at 15 1Ö1 and 2Ö2 km grids and at fixed depths of 30 cm and measured using the 16 flame atomic aqua regia absorption spectroscopy. The sampled concentrations were 17 interpolated using the regression-kriging interpolation technique with geological, 18 land cover maps, terrain parameters and industrialization parameters as auxiliary 19 predictors. The results showed that the best auxiliary predictors are geological map, 20 distance to water table, NDVI and slope map and distance to urban areas. The 21 spatial prediction was especially successful for Cd, Ni, Pb and Zn, and somewhat 22 less successful for Cu and Cr. The final map of cumulative limitation scores showed 23 that only 2% of the total agricultural area is absolutely clean from all heavy metals 24 (cumulative limitation scores <1). 22.9% of the total area is critically polluted by 25 one or more heavy metals (cumulative limitation scores >5). The advantage of using 26 limitation scores is that patches of high cumulative heavy-metal concentrations can 27 be visualized and quantified. In addition, the cumulative limitation scores can be 28 used directly in decision making

heavy metal concentration ; regression-kriging ; limitation score ; GIS

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