基于BP神经网络对某电镀厂土壤重金属预测及人体健康风险评价
Prediction of Soil Heavy Metals Based on BP Neural Network and Assessment of Human Health Risk of an Electroplating Plant
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摘要: 以江苏某已停产的电镀厂作为研究区，检测采样点重金属浓度，采用地质累积指数法、Matlab构建的back propagation (BP)神经网络预测模型、人体健康风险评价模型，分析深层土壤受重金属污染程度以及对人体的健康风险。结果表明，表层土壤中重金属超标主要集中在废水处理区、一车间，这可能是由于电镀作业产生的废水和灰渣导致的。通过BP神经网络预测模型可以看出，重金属Cr和As渗入深层土壤较为严重，深层土壤Cr和As的致癌风险处于不可接受水平。重金属Cr在表层土壤中致癌风险尤其显著，且非致癌风险超过了可接受水平。因此需重点关注研究区内Cr、As污染，为遗留地块再开发提供保障。Abstract: The pollution degree and the health risk of heavy metals in soil of electroplating factories located in Jiangsu Province was investigated. The concentration of heavy metals in soil samples were measured firstly, then it was deeply analyzed by means of geological accumulation index method, BP neural network prediction model and human health risk assessment model. The results showed that the excessive heavy metals in the topsoil were mainly concentrated in the wastewater treatment area and the first workshop, which may be caused by wastewater and ash generated in the electroplating process. In addition, the BP neural network prediction model showed that the infiltration of Cr and As into deep soil was very serious, and the carcinogenic risk of Cr and As in deep soil was at an unacceptable level. Moreover, the carcinogenic risk of heavy metal Cr was particularly significant in topsoil, and the non-carcinogenic risk exceeds the acceptable level. Therefore, it is necessary to pay attention to the pollution of Cr and As in the research area to provide a guarantee for the redevelopment of the legacy land.
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Key words:
- heavy metals /
- BP neural network /
- health risk /
- prediction
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