Evaluation and Prediction of Heavy Metal Health Risk in Soils Left Over from an Electroplating Plant in Zhejiang Province Based on BP Neural Network and Inverse-Distance Weighting
The study area was a derelict electroplating factory in Huzhou of Zhejiang Province,and the health risk of soil heavy metal pollution in the region by means of the Nemero index method and human health risk assess-ment models was undertaken to analyze the characteristics of the spatial distribution of soil heavy metal concentra-tion,in order to provide theoretical support for environmental pollution recovery of electroplating plant demolition.A BP(Back Propagation)neural network prediction model was constructed by MATLAB to forecast the human health risk of the heavy metal contamination in deep soil.At the same time,the inverse distance weight interpola-tion method in ArcGIS software was used to draw the distribution map of the predicted health risk.The results re-vealed that the studied area was largely contaminated by Cr and Ni.The carcinogenic risk of Cr in buried under-ground storage tanks was 0.35,which was a high risk for cancer.The excessive heavy metals in the surface soil were mainly concentrated in underground storage tank burial,galvanizing and nickel-plating workshops,and tem-porary waste accumulation areas,which may be caused by insufficient anti-seepage measures on the electroplating operation ground and improper disposal of electroplating waste.The constructed BP neural network prediction model showed that Cr,As,and Ni in the plot still have a carcinogenic risk in the deep soil at a depth of 2.0～2.5 m;Ni,Cr,As,Zn,Cu,and other elements no longer have non carcinogenic risks in the soil at a depth of 2.0～2.5 m.
heavy metalBP neural networkhealth risk evaluationspatial distribution
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