Chemical Form Distribution And Spatial Variationin Of Heavy Metals In Polluted Paddy Soils

At present, the heavy metal pollution in soils is an important issue for environmental science. At home and abroad, the studies of the spatial variation about soil quality mainly focused on soil moisture, bulk density, texture and nutrition such as soil organic matter , nitrogen, phosphor, kalium, pH et al. But in landscape and region scale the study on the spatial variation of available heavy metals in soil was scarce, which are necessary for soil environment rehabilitation.The polluted paddy soil around Guixi smelty in Jiangxi Province was studied by field survey and laboratory chemical analysis. The chemical forms of the polluted soil were analyzed, and the spatial variation was mapped. The data were explored using correlation analysis, ANOVA analysis and geostastical analysis.The study of chemical form analysis using BCR method was indicated that the pollution was heavier in slag filtrate (SP in abbreviation) polluted region than in waste water-irrigation (WW in abbreviation) pollution region. The pollution of Cu, Cd, Pb in SP was more seriously than that in WW, and Ni is on the contrary. The operationally defined fraction results indicated that Cu in surface layer (0-20cm) soils occurred mainly in organic matter bound fraction; soil Cd in exchangeable and carbonate bound fractions; soil Pb in two fractions: organic matter bound fraction and Fe and Mn oxide bound fraction; soil Ni in mineral fraction, i.e. residual fraction. The proportion of available fractions of soil heavy metals followed the sequence of Cd>Cu>Pb>Ni. The obvious correlation among the various fractions of soil between Cu, Pb, Cd and Ni, suggested that these metals were congenetic. Soil pH influenced the distribution of soil Cu in WW, as well as the exchangeable and carbonates bound Ni in WW. The validity of heavy metals were affected by soil absorb capability, especially Cu, Cd. However, soil organic matter content showed less influence.The semivariogram analysis of available heavy metals (ie Cu, Cd, Pb, Zn) by the methods of geostatistics combined with geographic information system was...