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 |
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Keywords
- Geographic Information System
- Kriging
- Soil Contamination
- Spatial Analysis
ASJC Scopus subject areas
- Public Health, Environmental and Occupational Health
Cite this
Identification of soil contamination in AnShen using a geographic information system. / Chiang, Po Huang; Hsieh, Dennis H.; Chen, Hsiao Hui; Chan, Ta Chien; Liou, De Ming; Wen, Chi Pang; Chen, Hsiao Lei; Mao, I. Fang.
In: Taiwan Journal of Public Health, Vol. 25, No. 5, 01.10.2006, p. 363-371.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Identification of soil contamination in AnShen using a geographic information system
AU - Chiang, Po Huang
AU - Hsieh, Dennis H.
AU - Chen, Hsiao Hui
AU - Chan, Ta Chien
AU - Liou, De Ming
AU - Wen, Chi Pang
AU - Chen, Hsiao Lei
AU - Mao, I. Fang
PY - 2006/10/1
Y1 - 2006/10/1
N2 - 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.
AB - 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.
KW - Geographic Information System
KW - Kriging
KW - Soil Contamination
KW - Spatial Analysis
UR - http://www.scopus.com/inward/record.url?scp=33846404209&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33846404209&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:33846404209
VL - 25
SP - 363
EP - 371
JO - 台灣公共衛生雜誌
JF - 台灣公共衛生雜誌
SN - 1023-2141
IS - 5
ER -