Spatial Distribution Characteristics And Impact Factors Of Soil Heavy Metal In Jiulongpo District

Through the analysis of the soil heavy metal samples, including Pb, Cd, As, Hg, this article analyzed the spatial variability and distribution characteristics of soil heavy metals in Jiulongpo district, using geostatistical analyst methods, random forest method, Nemerow index method, correlation analysis and cluster analysis methods, etc. The influences of different impact factors of soil heavy metals, including parent material, land use, physical and chemical properties, terrain, were discussed. And soil heavy metal pollution of Jiulongpo district was evaluated. The main conclusion of the study is as follows:(1) Through the analysis of the spatial variation of soil heavy metal in Jiulongpo district, we know that Pb and Cd have strong variabilities, while As and Hg have normal variabilities, and was in order of Cd > Pb > As > Hg. The optimal interpolation model was identified through global trend analysis and variation function fitting, Pb and Cd fit logarithmic transformation kriging, while As and Hg fit normal kriging. The content of Pb, As and Hg in Huayan town and Hangu town was much higher, and the content of Cd in Hangu town and Xipeng town was much higer.(2) Soil heavy metal content under different land use and geology type was analyzed, and the result showed that the differences were not obvious within paddy field, dry land, vegetable field and orchard. But the influence of geology type for the content of As was very significant.(3) The content of soil heavy metal was analyzed with pH, organic matter, alkali-hydrolyzale nitrogen, available phosphorus, available potassium, available zinc, available copper and available iron. The result showed that Pb was outstanding significant positive correlated with available copper and available iron, while was outstanding significant negative correlated with available phosphorus, and was significant positive correlated with pH and organic matter. Cd was outstanding significant positive correlated with organic matter, available copper and available zinc, and was significant positive correlated with pH. As was outstanding significant positive correlated with p H, organic matter, alkali-hydrolyzale nitrogen, available potassium and available copper, while was significant negative correlated with available zinc. Hg was outstanding significant positive correlated with organic matter, alkali-hydrolyzale nitrogen, available phosphorus, available zinc, while was outstanding significant negative correlated with pH.(4) K-means clustering method was used to analyze the relationship between terrain and soil heavy metal content, and DB(Davies Bouldin) value was used as the evaluation standard to identify the optimal clustering number. Terrain contained elevation, slope, surface curvature, plan curvature, profile curvature, topographic position index(TPI) and topographic wetness index(TWI). The result showed that Pb content increased with elevation gradually; Cd distributed much in valley, and less in ridge; As distributed much on the convergence and concave slope and close to valley, where soil water content is relatively high; Hg distributed much on the divergence and convex slope with higher elevation, where soil water content is relatively low.(5) Random forest algorithm was used to identify the relative importance of each impact factor on soil heavy metal. The training set and validation set were built for forecasting and testing. The result showed that, for Pb, the most influencing top 3 was available copper, available iron and pH. For Cd, the most influencing top 3 was available iron, available copper and available zinc. For As, the most influencing top 3 was pH, geology type and available copper. For Hg, the most influencing top 3 was available zinc, available phosphorus and pH.(6) Nemerow index method was used to evaluate the soil heavy metal pollution. The results of single factor index method showed that Pb content exceed standard, while the others were relatively normal. The results of comprehensive index method showed that the most of the districts were in a state of pollution-free, but about one third of the region was lightly polluted.