The Spatial Variance Analysis of Environmental Quality Monitoring Data

The statistics methods were used to analyze the environmental quality data, such as groundwater data and soil heavy metal content data, and hope to increase the value of those data. Using multivariate analysis and Geographic Information Systems (GIS) to analyze the groundwater quality data in Taiwan from 1993 to 2005 can find that there are five main factors for groundwater in Taiwan. Those factors are factor 1 (Saline Factor), factor 2 (Heavy Metal Pollution Factor), factor 3 (pH Factor), factor 4 (Organic Factor), and factor 5 (Manganese Factor). The cumulative percent of variance is 77.34%, the results and its cause are discussed. Use moving window method and semi-variogram to analyze the structure of Ni in Chang-Hwa. Find that the effect range of Ni in Chang-Hwa and find it is about 700m. Then, using regression analysis to find that there is contamination continuous occurring in Homei, and should be monitored. The arsenic contamination in Chinkuashih is caused by the smoke from mining industry. After using five statistics methods to analyze the univariate data, it shows that finite mixture model can get the effective classified group.