Tsun-Kuo Chang

Multivariate analysis of soil heavy metal pollution and landscape pattern in Changhua county in Taiwan

This study applied factor analysis and landscape indices of 55 sampling sites in Changhua county in Taiwan to characterize the factor patterns of eight soil heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb and Zn) and the interrelation patterns of these soil heavy metals, landscape and human activities. The landscape analysis results indicated that landscape indices can elucidate spatial landscape patterns, urbanization and industrialization, demonstrating that higher landscape diversity corresponded to a higher ratio of urban planning area to the number of industrial plants. Factor analyses revealed that soil heavy metals and data concerning landscape data could be grouped into a six-factor model that accounts for 82% of all the variation of data. Moreover, the first factor included the concentration of Cd, Cr, Cu, Ni and Zn, and urbanization and industrialization landscape indices. These variables together explained 34.5% of the variation in the concentration of the soil heavy metals and landscape indices data of this study area. Local urbanization and industrialization caused local soil pollution by heavy metals on the selected sampling sites in Changhua county in Taiwan. Geographic information system can fully display the spatial patterns and relationships among landscape indices and concentration of soil heavy metals in this study area.

Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan

This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil.

Possible association between nickel and chromium and oral cancer: A case–control study in central Taiwan

Oral cancer is one of the most common cancers in Taiwan. Changhua County, in central Taiwan, has an extremely high prevalence of oral cancer, along with a high concentration of metal-related industries and soil metal contamination. The aim of this study was to clarify the possible association between metals and oral cancer within this specific area. This study recruited 101 oral cancer patients and 104 controls from the Changhua Christian Hospital. All subjects completed a questionnaire that asked about demographic information; cigarette, alcohol, and betel quid use; and environmental and occupational exposure history. Blood samples were collected and tested for metal concentrations with inductively coupled plasma mass spectrometry. A multiple logistic regression model illustrated that oral cancer was significantly associated with the blood levels of nickel and chromium (both with P<0.0001) after controlling for potential confounders. This study suggested a potential role of these two metals in the mechanism of oral cancer development.

Arsenic and lead (beudantite) contamination of agricultural rice soils in the Guandu Plain of northern Taiwan.

This study investigates the species of As and Pb (beudantite) residues present in the seriously contaminated agricultural rice soils of the Guandu Plain. Two pedons in the Guandu Plain agricultural soils, each pedon separated into five horizons (each of 20 cm) were collected for this study. Soil samples were packed into a column for leaching with simulated acid rains. Soil pH ranged from 5.1 to 7.1 with high base saturation. Soils can be classified as clay loam, mixed, thermic, Typic or Umbric Albaqualfs. The XRD analysis indicated the beudantite particles are present in clay fractions, showing high concentrations of As and Pb. This is because of 50-100 years ago irrigation water was introduced from Huang Gang Creek of hot springs containing high concentrations of As and Pb. Only low concentrations of As and Pb can be leached out with simulated acid rains (i.e., pHs 2 and 4), even through 40 pore volumes of leaching experiments. The sequential extraction experiments resulted in the high portions of As and Pb remaining in the amorphous, Fe and Al oxyhydroxides and residual fractions. Thus, the remediation of As and Pb in this agricultural rice paddy soils merits further study.

Applying Factor Analysis Combined with Kriging and Information Entropy Theory for Mapping and Evaluating the Stability of Groundwater Quality Variation in Taiwan

In Taiwan many factors, whether geological parent materials, human activities, and climate change, can affect the groundwater quality and its stability. This work combines factor analysis and kriging with information entropy theory to interpret the stability of groundwater quality variation in Taiwan between 2005 and 2007. Groundwater quality demonstrated apparent differences between the northern and southern areas of Taiwan when divided by the Wu River. Approximately 52% of the monitoring wells in southern Taiwan suffered from progressing seawater intrusion, causing unstable groundwater quality. Industrial and livestock wastewaters also polluted 59.6% of the monitoring wells, resulting in elevated EC and TOC concentrations in the groundwater. In northern Taiwan, domestic wastewaters polluted city groundwater, resulting in higher NH3-N concentration and groundwater quality instability was apparent among 10.3% of the monitoring wells. The method proposed in this study for analyzing groundwater quality inspects common stability factors, identifies potential areas influenced by common factors, and assists in elevating and reinforcing information in support of an overall groundwater management strategy.

Spatiotemporal trends in oral cancer mortality and potential risks associated with heavy metal content in Taiwan soil.

Central and Eastern Taiwan have alarmingly high oral cancer (OC) mortality rates, however, the effect of lifestyle factors such as betel chewing cannot fully explain the observed high-risk. Elevated concentrations of heavy metals in the soil reflect somewhat the levels of exposure to the human body, which may promote cancer development in local residents. This study assesses the space-time distribution of OC mortality in Taiwan, and its association with prime factors leading to soil heavy metal content. The current research obtained OC mortality data from the Atlas of Cancer Mortality in Taiwan, 1972–2001, and derived soil heavy metals content data from a nationwide survey carried out by ROCEPA in 1985. The exploratory data analyses showed that OC mortality rates in both genders had high spatial autocorrelation (Moran’s I = 0.6716 and 0.6318 for males and females). Factor analyses revealed three common factors (CFs) representing the major pattern of soil pollution in Taiwan. The results for Spatial Lag Models (SLM) showed that CF1 (Cr, Cu, Ni, and Zn) was most spatially related to male OC mortality which implicates that some metals in CF1 might play as promoters in OC etiology.

Geostattstical analysis of soil arsenic content in taiwan

Abstract A combined geostatistical and Computergraphic approach was developed for illustrating the soil Arsenic map of Taiwan. Data were collected from the Environmental Protection Administrations study targeting agricultural soils in Taiwan. The range and arithmetic mean of the As contents in the surface soils (0 to 15 cm) of the study samples are as follows: 0.01 to 16.16, 5.65 (mg/kg dry soil). Variograms (Semivariograms) indicated spatial correlation at distances up to 195.0 km. The data exhibited some anisotropy, but this had little effect on kriging. An exponential variogram model was fitted using least squares and used to krige a grid covering Taiwan. Soils southwest of Taiwan tended to contain higher levels of As than average. The map will be useful in future research to determine the geographic distribution of regional patterns of plants and groundwater As content, the relationship between As and parent soil material, and correlation with of occurrence of blackfoot disease.

Simulated annealing and kriging method for identifying the spatial patterns and variability of soil heavy metal

Abstract Environmental data, including information regarding soil heavy metals, may contain significant uncertainty and exhibit a skewed distribution with a complex and unexplainable spatial variation. This study identified the spatial patterns and variations of soil heavy metals (Cu, Cd, Hg, and Pb) in the northern part of Changhua County in Taiwan to clarify the characteristics and pollution of soil heavy metals. The spatial maps of soil heavy metals were also estimated and simulated using kriging and simulated annealing methods. Correlation analysis indicated that Pearson and Spearman correlation coefficients among these four heavy metals were significant; between Cd and Cu, these two correlation coefficients were strongly significant. As expected, the spatial maps of estimation and simulation of soil heavy metals revealed high concentration areas of Cd, Cu along the main irrigation‐ditch system and surrounding industrial plants in the area of study. In addition to reproducing the spatial variation of the investigated Cd, Cu, Hg and Pb, simulated annealing could also identify the global spatial continuity and discontinuity patterns of soil heavy metals. Kriging and simulated annealing methods can both be applied to identify pollution sources and patterns for monitoring and remedy.

Lead isotope characterization of petroleum fuels in Taipei, Taiwan.

Leaded gasoline in Taiwan was gradually phased out from 1983 to 2000. However, it is unclear whether unleaded gasoline still contributes to atmospheric lead (Pb) exposure in urban areas. In this study, Pb isotopic compositions of unleaded gasolines, with octane numbers of 92, 95, 98, and diesel from two local suppliers in Taipei were determined by multi-collector inductively coupled plasma mass spectrometry with a two-sigma uncertainty of ± 0.02 %. Lead isotopic ratios of vehicle exhaust (208Pb/207Pb: 2.427, 206Pb/207Pb: 1.148, as estimated from petroleum fuels) overlap with the reported aerosol data. This agreement indicates that local unleaded petroleum fuels, containing 10–45 ng·Pb·g−1, are merely one contributor among various sources to urban aerosol Pb. Additionally, the distinction between the products of the two companies is statistically significant in their individual 208Pb/206Pb ratios (p-value < 0.001, t test). Lead isotopic characterization appears to be applicable as a “fingerprinting” tool for tracing the sources of Pb pollution.

GEOSTATISTICAL SIMULATION AND ESTIMATION OF THE SPATIAL VARIABILITY OF SOIL ZINC

Abstract Collected data in soil heavy metal investigations may contain significant levels of uncertainty, including complex and even unexplainable spatial variations at a small investigation site. Therefore, this study identifies the spatial structure of soil zinc in the northern part of Changhua County in Taiwan to understand the spatial variation and uncertainty of soil zinc. The spatial maps of this heavy metal are simulated by using the geostatistical simulation, and estimated by using ordinary kriging and natural log kriging. The estimation and simulation results indicate that Sequential Gaussian Simulations can reproduce the spatial structure for investigated data. Furthermore, displaying a low spatial variability, the ordinary kriging and natural log kriging estimates can not fit the spatial structure and small‐scale variation for the soil zinc investigated data. The maps of kriging estimates are much smoother than those of simulations. Sequential Gaussian Simulation with multiple realizations has significant advantages at a site with high variation investigated data over ordinary kriging, even natural log kriging techniques. Geographic information systems display these simulation and estimation results.