The John and Willie Leone Family Department of Energy and Mineral Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Chemosphere. 2013 Aug;92(9):1207-13. doi: 10.1016/j.chemosphere.2013.04.045. Epub 2013 May 25.
The spatial modeling of the petrochemical active regions in the Niger Delta (ND), Nigeria was carried out through the analysis exploration and extraction of geospatial data and resultant risk maps were generated. The pollutants assessed include; heavy metals, polychlorinated aromatic hydrocarbons (PAHs), benzene-toluene-ethylene-xylene (BTEX), and total petroleum hydrocarbons (TPHs) and properties of the pollutants such as bioaccumulation, persistence and toxicity were used to calculate the Hazard Index (HI) and thus created a ranking system. The Composite Risk Index (CRI) was developed successively considering the concentrations of all pollutants and the computed HI using the samples collected in ND areas of Nigeria. The carcinogenic PAHs showed spatial abundance in the areas sampled and elevated levels of soil heavy metals were also observed. In this study, mathematical tool such as the artificial neural network (ANN) self-organizing map (SOM) and geostatistical analysis such as kriging were applied to develop the risk map of the areas which represent the spatial spread of the CRI. The results show that the application of spatially developed integral risk map for pollutant assessment is effective and facilitates with decision making with regards the environment and humans exposed in this region.
通过分析探索和提取地理空间数据，对尼日利亚尼日尔三角洲（ND）的石化活动区域进行了空间建模，并生成了相应的风险图。评估的污染物包括：重金属、多氯代芳烃（PAHs）、苯-甲苯-乙烯-二甲苯（BTEX）和总石油烃（TPHs），以及污染物的特性，如生物累积性、持久性和毒性，用于计算危害指数（HI），从而建立了一个排名系统。综合考虑尼日利亚 ND 地区采集样本中所有污染物的浓度和计算出的 HI，成功开发了综合风险指数（CRI）。在这项研究中，应用了人工神经网络（ANN）自组织映射（SOM）等数学工具和克里金等地质统计学分析，以开发代表 CRI 空间分布的风险图。结果表明，应用空间开发的综合风险图进行污染物评估是有效的，并有助于针对该地区的环境和暴露在其中的人类做出决策。
