Abstract
Objectives: In a "superfund site" in Tainan City, Taiwan, soils are heavily polluted. Major pollutants include pentachlorophenol, dioxin, and mercury. The current study used a geographic information system (GIS) spatial interpolation method to analyze soil and sediment samples in this area and estimate the range and severity of pollution in areas in the An-Shun "superfund site" with respect to dioxin and mercury. Methods: Different Kriging methods were used to select the best model, based on the smallest standardized prediction (SPE) and root mean square standardized (RMSS) errors. Results: The Universal Kriging with Spherical and the Ordinary Kriging with Exponential models were shown to be the best models for estimating dioxin and mercury levels, respectively. Discussion: Our results confirmed the monitoring data generated by the Taiwan EPA and provide additional information to aid in targeting areas in need of immediate clean-up action. Better simulation results are expected as more data and better GIS methodologies become available.
| Original language | English |
|---|---|
| Pages (from-to) | 363-371 |
| Number of pages | 9 |
| Journal | Taiwan Journal of Public Health |
| Volume | 25 |
| Issue number | 5 |
| Publication status | Published - Oct 1 2006 |
| Externally published | Yes |
Keywords
- Geographic Information System
- Kriging
- Soil Contamination
- Spatial Analysis
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
UN SDGs
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