Zhang Chaosheng, Luo Lin, Xu Weilin, Ledwith Valerie
Department of Geography, National University of Ireland, Galway, Ireland.
Sci Total Environ. 2008 Jul 15;398(1-3):212-21. doi: 10.1016/j.scitotenv.2008.03.011. Epub 2008 Apr 28.
Pollution hotspots in urban soils need to be identified for better environmental management. It is important to know if there are hotspots and if the hotspots are statistically significant. In this study identification of pollution hotspots was investigated using Pb concentrations in urban soils of Galway City in Ireland as an example, and the influencing factors on results of hotspot identification were investigated. The index of local Moran's I is a useful tool for identifying pollution hotspots of Pb pollution in urban soils, and for classifying them into spatial clusters and spatial outliers. The results were affected by the definition of weight function, data transformation and existence of extreme values. Compared with the results for the positively skewed raw data, the transformed data and data with extreme values excluded revealed a larger area for the high value spatial clusters in the city centre. While it is hard to decide the best way of using this index, it is suggested that all these influencing factors should be considered until reasonable and reliable results are obtained. GIS mapping can be applied to help evaluate the results via visualization of the spatial patterns. Meanwhile, selected pollution hotspots (extreme values) in this study were confirmed by re-analyses and re-sampling.
为了更好地进行环境管理，需要识别城市土壤中的污染热点。了解是否存在热点以及这些热点在统计上是否显著非常重要。在本研究中，以爱尔兰戈尔韦市城市土壤中的铅浓度为例，对污染热点的识别进行了调查，并研究了影响热点识别结果的因素。局部莫兰指数是识别城市土壤中铅污染热点并将其划分为空间聚类和空间离群值的有用工具。结果受到权重函数定义、数据转换和极值存在的影响。与正偏态原始数据的结果相比，转换后的数据和排除极值的数据显示市中心高值空间聚类的面积更大。虽然很难确定使用该指数的最佳方法，但建议在获得合理可靠的结果之前，应考虑所有这些影响因素。地理信息系统（GIS）制图可通过空间模式可视化来帮助评估结果。同时，本研究中选定的污染热点（极值）通过重新分析和重新采样得到了证实。
